Overview

Dataset statistics

Number of variables83
Number of observations2946
Missing cells43075
Missing cells (%)17.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 MiB
Average record size in memory664.0 B

Variable types

Numeric6
Categorical76
Boolean1

Warnings

Process Date has constant value "2019-12-17T00:00:00.000" Constant
pymnt_plan has constant value "False" Constant
LOAN_AMT has a high cardinality: 492 distinct values High cardinality
Business Title has a high cardinality: 1244 distinct values High cardinality
Civil Service Title has a high cardinality: 312 distinct values High cardinality
Division/Work Unit has a high cardinality: 678 distinct values High cardinality
Job Description has a high cardinality: 1608 distinct values High cardinality
Minimum Qual Requirements has a high cardinality: 336 distinct values High cardinality
Preferred Skills has a high cardinality: 1282 distinct values High cardinality
Additional Information has a high cardinality: 681 distinct values High cardinality
To Apply has a high cardinality: 893 distinct values High cardinality
Hours/Shift has a high cardinality: 181 distinct values High cardinality
Posting Date has a high cardinality: 493 distinct values High cardinality
Posting Updated has a high cardinality: 487 distinct values High cardinality
DevType has a high cardinality: 810 distinct values High cardinality
CommunicationTools has a high cardinality: 348 distinct values High cardinality
EducationTypes has a high cardinality: 264 distinct values High cardinality
SelfTaughtTypes has a high cardinality: 226 distinct values High cardinality
HackathonReasons has a high cardinality: 98 distinct values High cardinality
LanguageWorkedWith has a high cardinality: 1578 distinct values High cardinality
LanguageDesireNextYear has a high cardinality: 1607 distinct values High cardinality
DatabaseWorkedWith has a high cardinality: 691 distinct values High cardinality
DatabaseDesireNextYear has a high cardinality: 819 distinct values High cardinality
PlatformWorkedWith has a high cardinality: 764 distinct values High cardinality
PlatformDesireNextYear has a high cardinality: 938 distinct values High cardinality
FrameworkWorkedWith has a high cardinality: 216 distinct values High cardinality
FrameworkDesireNextYear has a high cardinality: 363 distinct values High cardinality
IDE has a high cardinality: 839 distinct values High cardinality
Methodology has a high cardinality: 155 distinct values High cardinality
orignal_website_directory has a high cardinality: 2946 distinct values High cardinality
zip_code has a high cardinality: 629 distinct values High cardinality
earliest_cr_line has a high cardinality: 426 distinct values High cardinality
Time has a high cardinality: 698 distinct values High cardinality
your_favoritearticle_today has a high cardinality: 2945 distinct values High cardinality
url has a high cardinality: 2946 distinct values High cardinality
Email has a high cardinality: 1921 distinct values High cardinality
homeaddress has a high cardinality: 2629 distinct values High cardinality
officeaddress has a high cardinality: 2331 distinct values High cardinality
website has a high cardinality: 1369 distinct values High cardinality
CrimeTime has a high cardinality: 754 distinct values High cardinality
Residency Requirement is highly correlated with previousaddress and 5 other fieldsHigh correlation
previousaddress is highly correlated with Residency Requirement and 4 other fieldsHigh correlation
HackathonReasons is highly correlated with Residency Requirement and 1 other fieldsHigh correlation
YearsCoding is highly correlated with Age and 1 other fieldsHigh correlation
term is highly correlated with loan_status and 1 other fieldsHigh correlation
OperatingSystem is highly correlated with VersionControlHigh correlation
purpose is highly correlated with titleHigh correlation
next_pymnt_d is highly correlated with Residency Requirement and 2 other fieldsHigh correlation
Age is highly correlated with YearsCoding and 1 other fieldsHigh correlation
TimeAfterBootcamp is highly correlated with emp_lengthHigh correlation
emp_length is highly correlated with TimeAfterBootcamp and 1 other fieldsHigh correlation
dateAdded is highly correlated with Residency Requirement and 4 other fieldsHigh correlation
latitude is highly correlated with previousaddress and 3 other fieldsHigh correlation
Target_Salary is highly correlated with Residency Requirement and 1 other fieldsHigh correlation
YearsCodingProf is highly correlated with YearsCoding and 1 other fieldsHigh correlation
loan_status is highly correlated with term and 1 other fieldsHigh correlation
last_pymnt_amnt is highly correlated with next_pymnt_d and 1 other fieldsHigh correlation
last_credit_pull_d is highly correlated with last_pymnt_dHigh correlation
last_pymnt_d is highly correlated with term and 3 other fieldsHigh correlation
addr_state is highly correlated with next_pymnt_dHigh correlation
phones is highly correlated with Residency Requirement and 4 other fieldsHigh correlation
longitude is highly correlated with previousaddress and 3 other fieldsHigh correlation
title is highly correlated with purposeHigh correlation
VersionControl is highly correlated with OperatingSystemHigh correlation
PHONE is highly correlated with emp_lengthHigh correlation
AIResponsible is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
Residency Requirement is highly correlated with next_pymnt_d and 2 other fieldsHigh correlation
AIDangerous is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
previousaddress is highly correlated with pymnt_plan and 3 other fieldsHigh correlation
HackathonReasons is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
AgreeDisagree3 is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
YearsCoding is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
term is highly correlated with pymnt_plan and 3 other fieldsHigh correlation
OperatingSystem is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
LastNewJob is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
purpose is highly correlated with pymnt_plan and 2 other fieldsHigh correlation
next_pymnt_d is highly correlated with Residency Requirement and 6 other fieldsHigh correlation
Age is highly correlated with pymnt_plan and 2 other fieldsHigh correlation
TimeAfterBootcamp is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
FormalEducation is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
emp_length is highly correlated with next_pymnt_d and 3 other fieldsHigh correlation
HopeFiveYears is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
AIFuture is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
pymnt_plan is highly correlated with AIResponsible and 38 other fieldsHigh correlation
dateAdded is highly correlated with previousaddress and 3 other fieldsHigh correlation
YearsCodingProf is highly correlated with Age and 2 other fieldsHigh correlation
loan_status is highly correlated with term and 2 other fieldsHigh correlation
AgreeDisagree1 is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
UpdateCV is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
last_credit_pull_d is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
JobSearchStatus is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
UndergradMajor is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
AgreeDisagree2 is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
CompanySize is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
last_pymnt_d is highly correlated with term and 2 other fieldsHigh correlation
Target_Satisfied is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
addr_state is highly correlated with next_pymnt_d and 2 other fieldsHigh correlation
CheckInCode is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
TimeFullyProductive is highly correlated with next_pymnt_d and 2 other fieldsHigh correlation
phones is highly correlated with previousaddress and 3 other fieldsHigh correlation
AIInteresting is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
Process Date is highly correlated with AIResponsible and 38 other fieldsHigh correlation
title is highly correlated with purpose and 2 other fieldsHigh correlation
VersionControl is highly correlated with pymnt_plan and 1 other fieldsHigh correlation
PHONE is highly correlated with next_pymnt_d and 3 other fieldsHigh correlation
Preferred Skills has 393 (13.3%) missing values Missing
Additional Information has 1092 (37.1%) missing values Missing
Hours/Shift has 2062 (70.0%) missing values Missing
FormalEducation has 52 (1.8%) missing values Missing
UndergradMajor has 322 (10.9%) missing values Missing
DevType has 45 (1.5%) missing values Missing
YearsCodingProf has 408 (13.8%) missing values Missing
HopeFiveYears has 469 (15.9%) missing values Missing
JobSearchStatus has 435 (14.8%) missing values Missing
LastNewJob has 447 (15.2%) missing values Missing
UpdateCV has 857 (29.1%) missing values Missing
CommunicationTools has 923 (31.3%) missing values Missing
TimeFullyProductive has 894 (30.3%) missing values Missing
EducationTypes has 818 (27.8%) missing values Missing
SelfTaughtTypes has 1134 (38.5%) missing values Missing
TimeAfterBootcamp has 2725 (92.5%) missing values Missing
HackathonReasons has 2097 (71.2%) missing values Missing
AgreeDisagree1 has 813 (27.6%) missing values Missing
AgreeDisagree2 has 813 (27.6%) missing values Missing
AgreeDisagree3 has 807 (27.4%) missing values Missing
LanguageWorkedWith has 499 (16.9%) missing values Missing
LanguageDesireNextYear has 667 (22.6%) missing values Missing
DatabaseWorkedWith has 816 (27.7%) missing values Missing
DatabaseDesireNextYear has 1115 (37.8%) missing values Missing
PlatformWorkedWith has 876 (29.7%) missing values Missing
PlatformDesireNextYear has 1037 (35.2%) missing values Missing
FrameworkWorkedWith has 1313 (44.6%) missing values Missing
FrameworkDesireNextYear has 1215 (41.2%) missing values Missing
IDE has 586 (19.9%) missing values Missing
OperatingSystem has 569 (19.3%) missing values Missing
Methodology has 955 (32.4%) missing values Missing
VersionControl has 614 (20.8%) missing values Missing
CheckInCode has 627 (21.3%) missing values Missing
AIDangerous has 946 (32.1%) missing values Missing
AIInteresting has 870 (29.5%) missing values Missing
AIResponsible has 876 (29.7%) missing values Missing
AIFuture has 750 (25.5%) missing values Missing
Age has 919 (31.2%) missing values Missing
title has 64 (2.2%) missing values Missing
next_pymnt_d has 2610 (88.6%) missing values Missing
emp_length has 2231 (75.7%) missing values Missing
Email has 1005 (34.1%) missing values Missing
homeaddress has 317 (10.8%) missing values Missing
latitude has 317 (10.8%) missing values Missing
longitude has 317 (10.8%) missing values Missing
PHONE has 2231 (75.7%) missing values Missing
officeaddress has 539 (18.3%) missing values Missing
website has 547 (18.6%) missing values Missing
id is highly skewed (γ1 = -35.46636559) Skewed
Job Description is uniformly distributed Uniform
orignal_website_directory is uniformly distributed Uniform
your_favoritearticle_today is uniformly distributed Uniform
url is uniformly distributed Uniform
Email is uniformly distributed Uniform
homeaddress is uniformly distributed Uniform
officeaddress is uniformly distributed Uniform
id has unique values Unique
orignal_website_directory has unique values Unique
url has unique values Unique

Reproduction

Analysis started2021-06-21 06:12:44.479742
Analysis finished2021-06-21 06:13:56.999119
Duration1 minute and 12.52 seconds
Software versionpandas-profiling v3.0.0
Download configurationconfig.json

Variables

id
Real number (ℝ≥0)

SKEWED
UNIQUE

Distinct2946
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68306233.87
Minimum361774
Maximum68617057
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2021-06-21T11:43:57.159689image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum361774
5-th percentile67401305
Q168376221.5
median68465074.5
Q368537639.75
95-th percentile68606320.5
Maximum68617057
Range68255283
Interquartile range (IQR)161418.25

Descriptive statistics

Standard deviation1814269.389
Coefficient of variation (CV)0.02656081717
Kurtosis1322.387473
Mean68306233.87
Median Absolute Deviation (MAD)80364.5
Skewness-35.46636559
Sum2.01230165 × 1011
Variance3.291573417 × 1012
MonotonicityNot monotonic
2021-06-21T11:43:57.350318image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
679690241
 
< 0.1%
684960681
 
< 0.1%
683650051
 
< 0.1%
683752251
 
< 0.1%
684063351
 
< 0.1%
686168911
 
< 0.1%
685165401
 
< 0.1%
685861741
 
< 0.1%
686047311
 
< 0.1%
683854721
 
< 0.1%
Other values (2936)2936
99.7%
ValueCountFrequency (%)
3617741
< 0.1%
6995751
< 0.1%
654845531
< 0.1%
658557201
< 0.1%
658560591
< 0.1%
658859341
< 0.1%
658960701
< 0.1%
659165581
< 0.1%
659262731
< 0.1%
660558371
< 0.1%
ValueCountFrequency (%)
686170571
< 0.1%
686170341
< 0.1%
686169191
< 0.1%
686168911
< 0.1%
686168731
< 0.1%
686168671
< 0.1%
686168511
< 0.1%
686168251
< 0.1%
686167571
< 0.1%
686165881
< 0.1%

Target_Salary
Real number (ℝ≥0)

HIGH CORRELATION

Distinct519
Distinct (%)17.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58904.13979
Minimum0
Maximum218587
Zeros16
Zeros (%)0.5%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2021-06-21T11:43:57.571598image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile32.7
Q149390
median58440
Q373171.75
95-th percentile97360.83
Maximum218587
Range218587
Interquartile range (IQR)23781.75

Descriptive statistics

Standard deviation26986.57594
Coefficient of variation (CV)0.4581439612
Kurtosis3.939434558
Mean58904.13979
Median Absolute Deviation (MAD)11560
Skewness0.3859793367
Sum173531595.8
Variance728275280.7
MonotonicityNot monotonic
2021-06-21T11:43:57.761997image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5252482
 
2.8%
7500071
 
2.4%
5699068
 
2.3%
5541661
 
2.1%
6303149
 
1.7%
15.546
 
1.6%
5410046
 
1.6%
6994044
 
1.5%
6578343
 
1.5%
7000038
 
1.3%
Other values (509)2398
81.4%
ValueCountFrequency (%)
016
 
0.5%
8.752
 
0.1%
13.54
 
0.1%
154
 
0.1%
15.02242
 
0.1%
15.28782
 
0.1%
15.453
 
0.1%
15.546
1.6%
15.57472
 
0.1%
15.60212
 
0.1%
ValueCountFrequency (%)
2185872
 
0.1%
2095852
 
0.1%
2000002
 
0.1%
1985182
 
0.1%
1750006
0.2%
1641041
 
< 0.1%
1600006
0.2%
1577252
 
0.1%
1536664
0.1%
1503712
 
0.1%

Target_Satisfied
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
0
2327 
1
619 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters2946
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row1
3rd row0
4th row0
5th row1

Common Values

ValueCountFrequency (%)
02327
79.0%
1619
 
21.0%

Length

2021-06-21T11:43:58.175614image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:43:58.299906image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
02327
79.0%
1619
 
21.0%

Most occurring characters

ValueCountFrequency (%)
02327
79.0%
1619
 
21.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number2946
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
02327
79.0%
1619
 
21.0%

Most occurring scripts

ValueCountFrequency (%)
Common2946
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
02327
79.0%
1619
 
21.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII2946
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
02327
79.0%
1619
 
21.0%

LOAN_AMT
Categorical

HIGH CARDINALITY

Distinct492
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
$15,000.00
 
203
$10,000.00
 
188
$20,000.00
 
180
$12,000.00
 
158
$35,000.00
 
136
Other values (487)
2081 

Length

Max length11
Median length11
Mean length10.71792261
Min length10

Characters and Unicode

Total characters31575
Distinct characters14
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)10.0%

Sample

1st row$3,600.00
2nd row$24,700.00
3rd row$20,000.00
4th row$35,000.00
5th row$10,400.00

Common Values

ValueCountFrequency (%)
$15,000.00 203
 
6.9%
$10,000.00 188
 
6.4%
$20,000.00 180
 
6.1%
$12,000.00 158
 
5.4%
$35,000.00 136
 
4.6%
$24,000.00 101
 
3.4%
$5,000.00 99
 
3.4%
$8,000.00 93
 
3.2%
$18,000.00 82
 
2.8%
$6,000.00 81
 
2.7%
Other values (482)1625
55.2%

Length

2021-06-21T11:43:58.686304image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
15,000.00203
 
6.9%
10,000.00188
 
6.4%
20,000.00180
 
6.1%
12,000.00158
 
5.4%
35,000.00136
 
4.6%
24,000.00101
 
3.4%
5,000.0099
 
3.4%
8,000.0093
 
3.2%
18,000.0082
 
2.8%
6,000.0081
 
2.7%
Other values (482)1625
55.2%

Most occurring characters

ValueCountFrequency (%)
013723
43.5%
$2946
 
9.3%
,2946
 
9.3%
.2946
 
9.3%
2946
 
9.3%
11454
 
4.6%
21224
 
3.9%
51166
 
3.7%
3476
 
1.5%
8460
 
1.5%
Other values (4)1288
 
4.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number19791
62.7%
Other Punctuation5892
 
18.7%
Currency Symbol2946
 
9.3%
Space Separator2946
 
9.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
013723
69.3%
11454
 
7.3%
21224
 
6.2%
51166
 
5.9%
3476
 
2.4%
8460
 
2.3%
4420
 
2.1%
6382
 
1.9%
7306
 
1.5%
9180
 
0.9%
Other Punctuation
ValueCountFrequency (%)
,2946
50.0%
.2946
50.0%
Currency Symbol
ValueCountFrequency (%)
$2946
100.0%
Space Separator
ValueCountFrequency (%)
2946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common31575
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
013723
43.5%
$2946
 
9.3%
,2946
 
9.3%
.2946
 
9.3%
2946
 
9.3%
11454
 
4.6%
21224
 
3.9%
51166
 
3.7%
3476
 
1.5%
8460
 
1.5%
Other values (4)1288
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII31575
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
013723
43.5%
$2946
 
9.3%
,2946
 
9.3%
.2946
 
9.3%
2946
 
9.3%
11454
 
4.6%
21224
 
3.9%
51166
 
3.7%
3476
 
1.5%
8460
 
1.5%
Other values (4)1288
 
4.1%

Business Title
Categorical

HIGH CARDINALITY

Distinct1244
Distinct (%)42.2%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
Assistant Civil Engineer
 
33
Project Manager
 
29
College Aide
 
24
Construction Project Manager
 
22
ACCOUNTABLE MANAGER
 
20
Other values (1239)
2818 

Length

Max length115
Median length25
Mean length28.82654447
Min length4

Characters and Unicode

Total characters84923
Distinct characters70
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique263 ?
Unique (%)8.9%

Sample

1st rowAccount Manager
2nd rowEXECUTIVE DIRECTOR, BUSINESS DEVELOPMENT
3rd rowMaintenance Worker - Technical Services-Heating Unit
4th rowMaintenance Worker - Technical Services-Heating Unit
5th rowTemporary Painter

Common Values

ValueCountFrequency (%)
Assistant Civil Engineer33
 
1.1%
Project Manager29
 
1.0%
College Aide24
 
0.8%
Construction Project Manager22
 
0.7%
ACCOUNTABLE MANAGER20
 
0.7%
Confidential Investigator18
 
0.6%
Watershed Maintainer17
 
0.6%
Investigator17
 
0.6%
Prosecuting Attorney16
 
0.5%
Senior Project Manager15
 
0.5%
Other values (1234)2735
92.8%

Length

2021-06-21T11:43:59.103735image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
manager362
 
3.4%
analyst307
 
2.9%
of249
 
2.3%
assistant235
 
2.2%
engineer231
 
2.2%
director228
 
2.1%
207
 
1.9%
and207
 
1.9%
project202
 
1.9%
senior165
 
1.6%
Other values (942)8230
77.5%

Most occurring characters

ValueCountFrequency (%)
7757
 
9.1%
e6734
 
7.9%
i5584
 
6.6%
n5447
 
6.4%
t5313
 
6.3%
r4974
 
5.9%
a4685
 
5.5%
o4153
 
4.9%
s3348
 
3.9%
c2489
 
2.9%
Other values (60)34439
40.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter55739
65.6%
Uppercase Letter19874
 
23.4%
Space Separator7757
 
9.1%
Other Punctuation704
 
0.8%
Dash Punctuation236
 
0.3%
Decimal Number233
 
0.3%
Open Punctuation190
 
0.2%
Close Punctuation188
 
0.2%
Final Punctuation2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A2409
12.1%
E1913
 
9.6%
C1877
 
9.4%
S1679
 
8.4%
I1537
 
7.7%
T1322
 
6.7%
R1172
 
5.9%
P1137
 
5.7%
D961
 
4.8%
N946
 
4.8%
Other values (16)4921
24.8%
Lowercase Letter
ValueCountFrequency (%)
e6734
12.1%
i5584
10.0%
n5447
9.8%
t5313
9.5%
r4974
8.9%
a4685
8.4%
o4153
 
7.5%
s3348
 
6.0%
c2489
 
4.5%
l2246
 
4.0%
Other values (16)10766
19.3%
Other Punctuation
ValueCountFrequency (%)
,458
65.1%
/123
 
17.5%
&93
 
13.2%
.14
 
2.0%
'12
 
1.7%
#4
 
0.6%
Decimal Number
ValueCountFrequency (%)
273
31.3%
151
21.9%
349
21.0%
044
18.9%
412
 
5.2%
54
 
1.7%
Dash Punctuation
ValueCountFrequency (%)
-218
92.4%
18
 
7.6%
Space Separator
ValueCountFrequency (%)
7757
100.0%
Open Punctuation
ValueCountFrequency (%)
(190
100.0%
Close Punctuation
ValueCountFrequency (%)
)188
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin75613
89.0%
Common9310
 
11.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e6734
 
8.9%
i5584
 
7.4%
n5447
 
7.2%
t5313
 
7.0%
r4974
 
6.6%
a4685
 
6.2%
o4153
 
5.5%
s3348
 
4.4%
c2489
 
3.3%
A2409
 
3.2%
Other values (42)30477
40.3%
Common
ValueCountFrequency (%)
7757
83.3%
,458
 
4.9%
-218
 
2.3%
(190
 
2.0%
)188
 
2.0%
/123
 
1.3%
&93
 
1.0%
273
 
0.8%
151
 
0.5%
349
 
0.5%
Other values (8)110
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII84903
> 99.9%
Punctuation20
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7757
 
9.1%
e6734
 
7.9%
i5584
 
6.6%
n5447
 
6.4%
t5313
 
6.3%
r4974
 
5.9%
a4685
 
5.5%
o4153
 
4.9%
s3348
 
3.9%
c2489
 
2.9%
Other values (58)34419
40.5%
Punctuation
ValueCountFrequency (%)
18
90.0%
2
 
10.0%

Civil Service Title
Categorical

HIGH CARDINALITY

Distinct312
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
COMMUNITY COORDINATOR
 
182
AGENCY ATTORNEY
 
112
CIVIL ENGINEER
 
87
CITY RESEARCH SCIENTIST
 
83
CONSTRUCTION PROJECT MANAGER
 
72
Other values (307)
2410 

Length

Max length30
Median length24
Mean length23.25526137
Min length4

Characters and Unicode

Total characters68510
Distinct characters49
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)0.8%

Sample

1st rowCONTRACT REVIEWER (OFFICE OF L
2nd rowADMINISTRATIVE BUSINESS PROMOT
3rd rowMAINTENANCE WORKER
4th rowMAINTENANCE WORKER
5th rowPAINTER

Common Values

ValueCountFrequency (%)
COMMUNITY COORDINATOR182
 
6.2%
AGENCY ATTORNEY112
 
3.8%
CIVIL ENGINEER87
 
3.0%
CITY RESEARCH SCIENTIST83
 
2.8%
CONSTRUCTION PROJECT MANAGER72
 
2.4%
CLERICAL ASSOCIATE72
 
2.4%
COMMUNITY ASSOCIATE69
 
2.3%
ADMINISTRATIVE PROJECT MANAGER58
 
2.0%
COMPUTER SYSTEMS MANAGER57
 
1.9%
ADMINISTRATIVE STAFF ANALYST (53
 
1.8%
Other values (302)2101
71.3%

Length

2021-06-21T11:43:59.473713image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
administrative413
 
5.0%
associate313
 
3.8%
manager312
 
3.8%
community288
 
3.5%
engineer277
 
3.4%
analyst252
 
3.1%
project241
 
2.9%
city190
 
2.3%
coordinator190
 
2.3%
agency181
 
2.2%
Other values (396)5525
67.5%

Most occurring characters

ValueCountFrequency (%)
E6406
9.4%
I6289
9.2%
A6267
 
9.1%
T6225
 
9.1%
5242
 
7.7%
N5030
 
7.3%
S4615
 
6.7%
R4582
 
6.7%
C4234
 
6.2%
O3911
 
5.7%
Other values (39)15709
22.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter62099
90.6%
Space Separator5242
 
7.7%
Open Punctuation573
 
0.8%
Close Punctuation357
 
0.5%
Dash Punctuation98
 
0.1%
Other Punctuation67
 
0.1%
Decimal Number46
 
0.1%
Lowercase Letter28
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
E6406
10.3%
I6289
10.1%
A6267
10.1%
T6225
10.0%
N5030
8.1%
S4615
 
7.4%
R4582
 
7.4%
C4234
 
6.8%
O3911
 
6.3%
M2574
 
4.1%
Other values (16)11966
19.3%
Lowercase Letter
ValueCountFrequency (%)
m6
21.4%
s4
14.3%
e4
14.3%
v4
14.3%
t2
 
7.1%
o2
 
7.1%
r2
 
7.1%
g2
 
7.1%
w2
 
7.1%
Other Punctuation
ValueCountFrequency (%)
/19
28.4%
&15
22.4%
'13
19.4%
#10
14.9%
,6
 
9.0%
.4
 
6.0%
Decimal Number
ValueCountFrequency (%)
225
54.3%
119
41.3%
31
 
2.2%
51
 
2.2%
Space Separator
ValueCountFrequency (%)
5242
100.0%
Open Punctuation
ValueCountFrequency (%)
(573
100.0%
Dash Punctuation
ValueCountFrequency (%)
-98
100.0%
Close Punctuation
ValueCountFrequency (%)
)357
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin62127
90.7%
Common6383
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
E6406
10.3%
I6289
10.1%
A6267
10.1%
T6225
10.0%
N5030
8.1%
S4615
 
7.4%
R4582
 
7.4%
C4234
 
6.8%
O3911
 
6.3%
M2574
 
4.1%
Other values (25)11994
19.3%
Common
ValueCountFrequency (%)
5242
82.1%
(573
 
9.0%
)357
 
5.6%
-98
 
1.5%
225
 
0.4%
119
 
0.3%
/19
 
0.3%
&15
 
0.2%
'13
 
0.2%
#10
 
0.2%
Other values (4)12
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII68510
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
E6406
9.4%
I6289
9.2%
A6267
 
9.1%
T6225
 
9.1%
5242
 
7.7%
N5030
 
7.3%
S4615
 
6.7%
R4582
 
6.7%
C4234
 
6.2%
O3911
 
5.7%
Other values (39)15709
22.9%

Division/Work Unit
Categorical

HIGH CARDINALITY

Distinct678
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
Executive Management
 
56
Central Brookly City Operation
 
36
Law Department
 
32
Administration
 
31
Citywide Cybersecurity
 
29
Other values (673)
2762 

Length

Max length30
Median length22
Mean length21.29633401
Min length2

Characters and Unicode

Total characters62739
Distinct characters76
Distinct categories11 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)4.0%

Sample

1st rowStrategy & Analytics
2nd rowTech Talent Pipeline
3rd rowManagement Services Department
4th rowManagement Services Department
5th rowDept of Management & Planning

Common Values

ValueCountFrequency (%)
Executive Management56
 
1.9%
Central Brookly City Operation36
 
1.2%
Law Department32
 
1.1%
Administration31
 
1.1%
Citywide Cybersecurity29
 
1.0%
Default28
 
1.0%
Green Infrastructure25
 
0.8%
W S/Connections Permitting25
 
0.8%
Dept of Environment Protection24
 
0.8%
Information Technology24
 
0.8%
Other values (668)2636
89.5%

Length

2021-06-21T11:43:59.795513image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
396
 
4.7%
office241
 
2.9%
management199
 
2.4%
of191
 
2.3%
executive130
 
1.5%
services105
 
1.2%
information83
 
1.0%
department80
 
1.0%
dept73
 
0.9%
and72
 
0.9%
Other values (880)6840
81.3%

Most occurring characters

ValueCountFrequency (%)
5518
 
8.8%
e5272
 
8.4%
n4546
 
7.2%
t4193
 
6.7%
i4053
 
6.5%
a3410
 
5.4%
r3235
 
5.2%
o3088
 
4.9%
s2392
 
3.8%
c1879
 
3.0%
Other values (66)25153
40.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter44601
71.1%
Uppercase Letter10717
 
17.1%
Space Separator5518
 
8.8%
Other Punctuation1118
 
1.8%
Dash Punctuation521
 
0.8%
Decimal Number99
 
0.2%
Open Punctuation77
 
0.1%
Close Punctuation77
 
0.1%
Connector Punctuation8
 
< 0.1%
Final Punctuation2
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C1285
12.0%
S976
 
9.1%
P856
 
8.0%
O808
 
7.5%
E792
 
7.4%
A779
 
7.3%
M742
 
6.9%
D659
 
6.1%
I535
 
5.0%
B530
 
4.9%
Other values (16)2755
25.7%
Lowercase Letter
ValueCountFrequency (%)
e5272
11.8%
n4546
10.2%
t4193
 
9.4%
i4053
 
9.1%
a3410
 
7.6%
r3235
 
7.3%
o3088
 
6.9%
s2392
 
5.4%
c1879
 
4.2%
l1737
 
3.9%
Other values (16)10796
24.2%
Decimal Number
ValueCountFrequency (%)
129
29.3%
216
16.2%
611
 
11.1%
410
 
10.1%
39
 
9.1%
09
 
9.1%
86
 
6.1%
55
 
5.1%
72
 
2.0%
92
 
2.0%
Other Punctuation
ValueCountFrequency (%)
/444
39.7%
&345
30.9%
.162
 
14.5%
,68
 
6.1%
'50
 
4.5%
:45
 
4.0%
#4
 
0.4%
Space Separator
ValueCountFrequency (%)
5518
100.0%
Dash Punctuation
ValueCountFrequency (%)
-521
100.0%
Open Punctuation
ValueCountFrequency (%)
(77
100.0%
Close Punctuation
ValueCountFrequency (%)
)77
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_8
100.0%
Final Punctuation
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin55318
88.2%
Common7421
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e5272
 
9.5%
n4546
 
8.2%
t4193
 
7.6%
i4053
 
7.3%
a3410
 
6.2%
r3235
 
5.8%
o3088
 
5.6%
s2392
 
4.3%
c1879
 
3.4%
l1737
 
3.1%
Other values (42)21513
38.9%
Common
ValueCountFrequency (%)
5518
74.4%
-521
 
7.0%
/444
 
6.0%
&345
 
4.6%
.162
 
2.2%
(77
 
1.0%
)77
 
1.0%
,68
 
0.9%
'50
 
0.7%
:45
 
0.6%
Other values (14)114
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII62736
> 99.9%
Punctuation2
 
< 0.1%
Specials1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5518
 
8.8%
e5272
 
8.4%
n4546
 
7.2%
t4193
 
6.7%
i4053
 
6.5%
a3410
 
5.4%
r3235
 
5.2%
o3088
 
4.9%
s2392
 
3.8%
c1879
 
3.0%
Other values (64)25150
40.1%
Specials
ValueCountFrequency (%)
1
100.0%
Punctuation
ValueCountFrequency (%)
2
100.0%

Job Description
Categorical

HIGH CARDINALITY
UNIFORM

Distinct1608
Distinct (%)54.6%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
The New York City Taxi and Limousine Commission (TLC) is the agency responsible for regulating New York City's taxicab and for-hire vehicle industry. TLC licenses and regulates over 130,000 vehicles and more than 175,000 drivers, making it the most active taxi and limousine regulatory agency in the United States. Aside from vehicles and drivers, TLC also regulates taxicab agents and for-hire vehicle bases, including popular app-based transportation services. The TLC plays a pivotal role in furthering public safety within New York City and is a lead agency in a citywide effort to reduce traffic-related injuries. One of the largest components of TLC’s operations is the enforcement of agency and administrative code regulations. The Prosecution Division investigates and prosecutes all summonses issued by TLC which consist of administrative, field and consumer-initiated complaints. Our division prosecutes a wide range of violations including reckless driving, unlicensed operation, illegal street pickups, harassment and leaving the scene of an accident. Prosecuting Attorneys represent TLC on cases heard before the Hearings Division of the Office of Administrative Trials and Hearings and will gain robust hands-on litigation experience as they rotate through various prosecutorial assignments, including Consumer Intake, Settlements, Hearings and Appeals. Duties and responsibilities will include, but are not limited to: • Managing a daily caseload and independently representing the Taxi and Limousine Commission at administrative hearings, including preparing and presenting witnesses and evidence at trial. • Evaluating case strengths and weaknesses to effectively negotiate plea and settlement agreements with respondents and/or their attorneys or representatives. • Interviewing consumer complainants to obtain complaint details and determine appropriate charging violations and settlement offers. • Reviewing hearing dispositions for summonses dismissed at OATH; drafting appeals and Chair petitions when appropriate.
 
14
The New York City Taxi and Limousine Commission (TLC) is the City agency responsible for oversight of the for-hire vehicle industries in New York City, which Include yellow medallion taxis, green Boro taxis, community car services and livery cars, black cars services, luxury limousines, commuter vans and Para-transit services. Combined, TLC regulates Industries that are responsible for over 800,000 daily trips. Our role is to ensure that each passenger's riding experience is safe comfortable and convenient and that TLC drivers are driving safely. Under direction of the Executive leadership of the TLC Uniformed Services Bureau, the Enforcement Deputy Chief will: • Oversee enforcement squads assigned to the overnight shift that conduct patrol and other enforcement operations citywide. • Provide training and mentoring for all rank levels. • Partner with other law enforcement agencies and industry stakeholders when developing enforcement strategies. • Develop and manage a unified approach to addressing illegal for-hire activity, utilizing enforcement statistics to determine performance measures. • Utilize enforcement statistics and for-hire trip data to identify trends that will inform staff deployment and enforcement strategies. • Present at internal and external meetings/briefing on Enforcement Division performance. • Deputy Chief will make changes to deployment strategies and squad assignments ensuring the Enforcement Division capability to carry out its mission and responsibilities in an exemplary manner. • Deputy Chief will be responsible for other management projects and responsibilities as determined by Uniformed Services Bureau Leadership. • Author Division memos related to disciplinary action and unusual incidents; tactical plans and review all written documentation drafted by junior supervisory staff. • Conduct initial internal investigations regarding the behavior of staff in violation of agency policy which may impact employee’s Special Patrolmen status with the NYPD. • Attend community meeting (i.e. precinct community council meetings, town halls, inter-agency operation meetings, etc.). • Inform staff of current directives and orders • Responsible for serviceability, proper care and use of equipment, patrol and administrative record keeping. • Responsible for conducting annual and probationary performance evaluations. • Instruct and frequently test the knowledge of staff regarding their duties and responsibilities. • Be available via agency mobile device 24/7 to senior leadership and direct reports. • Conduct frequent uniform inspections of staff including equipment and general appearance in the field while on patrol. • Review activity of squads assigned daily, monthly, quarterly and annually. • Provide formal orientation for newly promoted and assigned Captains and Lieutenants. • Dotted line oversight over Division Radio Command Operations Desk (aka Central). • Initiate disciplinary process as needed.
 
6
The NYC Mayor’s Office of Environmental Remediation (OER) designs and implements the City’s brownfield cleanup and redevelopment initiatives. Foremost among these is the NYC Voluntary Cleanup Program (NYC VCP), the nation’s first municipally-run cleanup program, which offers remedial oversight and liability protection to property owners and developers of over 80 sites each year. Brownfields are sites where redevelopment is complicated by the presence of contamination, such as from prior site uses, historic fill, or chemical spills. The office manages the NYC Clean Soil Bank that arranges the reuse of clean soil from deep excavations to provide substantial financial and environmental benefits. OER also supports Community Brownfield Planning Areas and administers the Brownfield Incentive Grant (BIG) program, which provides funding for the investigation and cleanup of brownfield sites as well as grants to community-based organizations conducting planning around brownfields. Additional OER programs and initiatives include the E-Designation Review Program for hazardous materials, air quality, and noise; Green Property Certification; and community engagement activities. To learn more about OER, please visit www.nyc.gov/oer. OER seeks a Project Manager to perform professional scientific work in engineering geology and geology on project sites under the E-Designation and City’s Voluntary Cleanup program. Duties will include but are not limited to: • Implement applicable laws and regulations and policy to meet Mayor’s Office, DEP, and OneNYC strategic environmental, remedial and engineering goals. • Become fluent in all OER Environmental Quality programs (NYC VCP, E-Designation Hazmat, Noise and Air) and other OER Programs including JumpStart, BIG Grants, Brownfield Partnership, Green Team, Green Property Certification, SPEED, EPIC, Clean Soil Bank, PURE Soil NYC and be prepared to provide assistance and answer questions from public. • Review plans, reports and schedules prepared by consultants, contractors, and agencies, and produce engineering analyses to assure technical quality and conformance with project completion dates, as well as with technical, programmatic, and regulatory considerations. • Conduct communications with development teams, the general public, elected officials, the press and other city agencies in accordance with OER, Mayor’s Office and DEP policies. • Oversee, inspect, and participate in field sampling and remediation, and oversee engineering activities. • Maintains databases and archives established by OER management for oversight of programs.
 
4
The Family Court Division is currently seeking applicants for the position of Assistant Borough Chief (ABC)/RTA Transfer Supervisor in the Division’s Juvenile Delinquency Prosecution Unit. The Family Court Division’s Juvenile Delinquency Prosecution Unit investigates, and prosecutes where appropriate, juvenile delinquency matters involving youth ages 7 to 17 who have been arrested for conduct that would constitute a crime if they were an adult. In accordance with recently enacted Raise the Age legislation, the division also investigates and prosecutes matters involving 16 and 17-year-olds in misdemeanor cases that originate in Family Court and felony cases which begin in the Youth Part of the Superior Court and are transferred to Family Court. The Family Court Division’s Juvenile Delinquency Prosecution Unit seeks to ensure that those youth who commit delinquent acts are held accountable for their misconduct and receive appropriate services. The Family Court system is focused on rehabilitation. The qualified applicants will be assigned to a borough based on borough needs. The primary responsibility of the ABC/RTA Transfer Supervisor will be to supervise and manage the flow of cases originating in the Youth Part. These responsibilities may include, but are not limited to: • Conferring with the District Attorney’s Office in the assigned borough regarding adolescent offender cases for purposes of compiling paperwork on adolescent offender cases and obtaining a copy of their file where a case is being removed/transferred to Family Court; • Conducting court appearances and supervising attorneys on cases being removed/transferred to Family Court when a bridge order of protection is requested; • Preparing, analyzing, and utilizing statistical data with respect to cases originating in the Youth Part; • Supervising support professionals assigned to assist with the flow of cases originating in the Youth Part; • Working and supervising in an overall fast-paced environment. Additional duties in Family Court may include, but are not limited to: • Supervising and training multiple staff attorneys; overseeing their cases from referral through disposition both in and out of the courtroom; • Providing legal and strategic advice to staff attorneys on their cases; • Assisting the Borough Chief, Deputy Borough Chief(s), and Assistant Borough Chief(s) with office initiatives and administrative duties; • Conducting case reviews, transcript reviews, and court observations; • Identifying, recommending, and referring matters for diversion; • Working with victims and advocating on their behalf; • Developing an understanding of New York City communities and the concerns of those who live in them by maintaining a consistent presence in these communities, and collaborating with community stakeholders to prevent and address juvenile delinquency; • Assisting staff attorneys in the identification, recommendation, and negotiation of matters appropriate for plea resolution; • Reviewing and editing written work, including petitions, supporting depositions, motions, and Memoranda of Law; • Reviewing court orders including, but not limited to motion decisions; • Ensuring the accurate data entry of litigation events; • Conducting courtroom observations and providing feedback to staff attorneys; • Assisting with training legal staff and support professionals; • Supervising support professionals; • Maintaining an active caseload; • Preparing, analyzing and utilizing statistical data; • Developing and maintaining collaborative relationships with all Division supervisors; • Writing, reviewing, and editing yearly performance evaluations for staff attorneys and support staff; • Assisting in the development and implementation of borough and Division-wide policies, procedures and protocols; • Representing the Division at interagency committee meetings; • Serving as a liaison to city and statewide agencies including but not limited to the NYPD, the District Attorneys’ Offices, the Department of Probation and the Administration of Children’s Services; • Conducting regular meetings with management or managerial staff, staff attorneys, and support professionals; • Drafting, reviewing, and monitoring performance enhancement and improvement plans. • Participating in a city-wide on-call system for juvenile offenses that take place during evening and weekend hours; • Working on cases and other responsibilities, including visiting crime scenes, in the evening and weekend hours; • Attending community events and meetings, including in the evening and weekend hours. ** This position will periodically involve participation in a citywide rotation of night/weekend court assignments. **
 
4
The Department of Citywide Administrative Services’ (“DCAS”) Division of Energy Management (“DEM”) serves as the hub for energy management for City government operations. Today, we develop the City’s annual Heat, Light, and Power Budget; manage the City’s electricity, natural gas, and steam accounts; help our agency partners identify and pursue energy-saving opportunities at their buildings; do energy efficiency and clean power generation projects across the City’s portfolio; and implement operations and maintenance (O&M) best practices. DEM is tasked with leading the City’s efforts to reduce greenhouse gas (“GHG”) emissions by 80 percent by 2050 from a 2005 baseline (“80x50”). As part of Local Law 97, the City also recently set new targets to reduce emissions from City government operations by 40 percent by 2025 (“40x25”) and by 50 percent by 2030 (“50x30”). To meet these goals, DEM is committed to collaborating very closely with our agency partners to help them achieve major emissions reductions in their buildings. We actively are working to provide our agency partners with the energy efficiency and clean energy project funding, project delivery vehicles, technical expertise, staff resources, strategic planning support, and data analytics that they need to succeed. DEM seeks to hire a Project Manager, Capital Project Implementation to serve within our Operations Unit. The Project Manager will oversee the implementation of diverse energy efficiency projects. The person’s primary responsibility will be to manage consultants and contractors who are engaged in the design and construction of energy efficiency capital projects at City facilities. With wide latitude for the exercise of independent judgment and initiative, the Project Manager, Capital Project Implementation will be charged with the following responsibilities: • Managing energy efficiency project scoping: Develops and reviews scopes of work for energy efficiency projects, working closely with contractors and consultants. Reviews completed Energy Audits and Energy Efficiency Reports (EERs) for buildings to help guide project selection and alternatives analysis. • Managing the design and construction process for energy efficiency projects: In close collaboration with contractors and consultants, manages the execution of design and construction for a sizable portfolio of energy-related capital projects. Ensures that projects are completed in a timely, cost-effective manner. Reviews, provides comments, and makes recommendations on design packages submitted by consultants for proposed energy efficiency projects. • Performing technical calculations to verify estimated project energy usage, energy cost, and emissions: Performs engineering calculations and energy modeling to verify the reasonableness and accuracy of estimated energy usage reductions, energy cost savings, and avoided greenhouse gas emissions for proposed energy efficiency projects. • Performing site visits throughout the project implementation process: Conducts field visits to assess energy usage reduction opportunities at City buildings; refine proposed scopes of work; facilitate consultants and contractors’ walk-throughs with agency staff; ensure project compliance with the scope and schedule set forth in contract documents; and perform measurement and verification activities. • Conducting measurement and verification activities: Performs measurement and verification tasks to assess realized savings from completed energy efficiency projects. • Coordinating with agency partners, consultants, and contractors: As designated, represents DEM in meetings with different City agencies, consultants, and contractors involved in energy efficiency project implementation. • Performing program data collection, tracking, and reporting: Performs program data collection and tracking required to ensure accurate, on-demand project reporting in a range of areas, including compliance with project schedule, budgets, and scopes; measurement and verification of energy savings and avoided emissions; and projects’ contributions towards the City’s goals. Maintains relevant DEM project tracking databases.
 
4
Other values (1603)
2914 

Length

Max length10647
Median length2251.5
Mean length2429.488119
Min length166

Characters and Unicode

Total characters7157272
Distinct characters110
Distinct categories17 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique369 ?
Unique (%)12.5%

Sample

1st rowDivision of Economic & Financial Opportunity (DEFO) Mayor Michael R. Bloomberg and SBS are committed to encouraging a competitive and diverse New York City business environment by promoting the growth and success of minority and women-owned companies. New York City’s Minority and Women-owned Business Enterprise (M/WBE) program is designed to help these historically underserved groups become more competitive. JOB DESCRIPTION The Account Manager will provide a range of supportive services to City agency purchasing personnel and private-sector prime contractors to help them comply with M/WBE utilization goals under Local Law 129. The Account Manager will oversee a portfolio of several City agencies and will be responsible for the monitoring and oversight of the strategies which have been broadly laid out for agencies to increase M/WBE utilization. The primary objective for the Account Manager is to help agencies increase the number and dollar value of contracts awarded to M/WBE at various contract levels. Specifically, the Account Manager will seek to bring agencies into compliance with the Citywide utilization goals and other metrics used for measuring agency performance. Each account manager will be responsible for procurements of all sizes and methods for their respective agencies. The Account Manager will report to the Director of Procurement Initiatives. Account Manager Model Each agency has very specific vendor requirements and needs, as well as obstacles to increasing M/WBE Utilization. The account managers will learn what is procured, by what method, how frequently, and how to get more M/WBEs participating in the process. The account manager will leverage their procurement contacts to work directly with program end users to identify needs and obstacles and create appropriate solutions. The Account Manager’s responsibilities will include the following: 1. Research agency procurement practices, requirements, in order to connect M/WBE firms with future procurement opportunities 2. Work with the agency senior staff to implement strategies to increase M/WBE participation 3. Introduce new M/WBE firms to agency staff 4. Assist agency staff with tools to improve performance, including monitoring prime contractor performance relating to M/WBE subcontractor utilization goals 5. Inform agency senior staff of their performance against goals on a regular basis 6. Assist program and procurement staff with program implementation questions as they arise 7. Produce analysis of agency contracts and M/WBE program performance 8. Coordinate resources for agencies as necessary, including networking events, training sessions, etc.
2nd rowThe New York City Department of Small Business Services (SBS) is a vibrant, client-centered agency whose mission is to serve New York’s small businesses, jobseekers and commercial districts. SBS makes it easier for companies in New York City to start, operate, and expand by providing direct assistance to business owners, supporting commercial districts, promoting financial and economic opportunity among minority- and women-owned businesses, preparing New Yorkers for jobs, and linking employers with a skilled and qualified workforce. SBS continues to reach for higher professional standards through innovative systems, new approaches to government, and a strong focus on its employees. NYC Business Solutions is a set of services offered by the NYC Department of Small Business Services to help businesses start, operate, and expand in New York City. All services are offered at no cost and are available to businesses of any size and at any stage. Services can be accessed through the city’s 7 NYC Business Solutions Centers, 6 Career Centers, and 3 Sector Centers located throughout the 5 boroughs. In 2010, NYC Business Solutions provided services to over 10,000 business customers located throughout the five boroughs. The Executive Director of Business Development will lead agency efforts to acquire new business customers and to increase the number of NYC Business Solutions services utilized by existing customers. The Executive Director is responsible for developing the business development strategy for all NYC Business Solutions services and ensuring effective implementation through the management of internal and external sales resources. The Executive Director will provide direct supervision to 3 Senior Account Managers and will oversee 16 sales teams in the field (70 total field staff). The Executive Director will also lead the professional development program for all staff engaging directly with business customers and is responsible for collaborating with the NYC Business Solutions marketing team to improve brand recognition throughout the five boroughs. Specific responsibilities include: Develop and execute the Agency’s business development strategy for all NYC Business Solutions services Identify business targets and coordinate sales efforts across sales teams to ensure efficient usage of system-wide resources Manage sales teams to meet their quarterly and annual sales goals through quarterly business development planning meetings and regular check-ins Directly supervise three Senior Account Managers and oversee approximately 70 field staff located at the city’s 7 NYC Business Solutions Centers, 6 Career Centers, and 3 Sector Centers Track and analyze system sales activities using Oracle CRM On Demand Collaborate with NYC Business Solutions and Workforce1 program management teams to link sales activity and service delivery Identify and create sales tools that enable sales teams to more effectively sell NYC Business Solutions services Design and implement the professional development program for all business facing staff Develop curriculum and lead sales training sessions for new and existing staff Organize and lead industry knowledge sessions with sector experts to deepen sales teams’ understanding of business prospects Lead sector focused working groups to build industry expertise and disseminate best practices across sales teams Increase awareness of NYC Business Solutions Services throughout the five boroughs of New York City Assist the marketing team to develop brochures, flyers, and advertisements to promote NYC Business Solutions services and events Participate in panel discussions and deliver public presentations at events Establish partnerships with non-profit organizations, government agencies, and the private sector to generate referrals for NYC Business Solutions services Preferred Skills: The ideal candidate will have demonstrated success developing and implementing business driven programs and will have exhibited: Strong management and leadership skills Experience planning, implementing and managing projects involving diverse stakeholders Extensive private or public sector experience in business development and sales The ability to organize and drive projects to timely completion The ability to actively listen and synthesize disparate viewpoints into a shared vision The ability to handle complexity in fast-paced entrepreneurial environments The ability to communicate effectively with a diverse array of internal and external stakeholders The ability to combine attention to detail with a clear understanding of the big picture Outstanding presentation, writing, and communications skills Outstanding analytical, problem solving, presentation and creative thinking abilities Excellent MS Excel, Word and Power Point skills Experience with Oracle CRM On Demand, SalesForce, or other customer relationship management tool preferred but not required Foreign language skills a plus
3rd rowUnder direct supervision, assist in the routine maintenance operation and repair of public buildings, structures, and the equipment they contain; perform related work. Responsibilities include, but are not limited to the following: 1. Perform minor and major repairs to boilers, burners, vacuum tank, pumps, motors and other various heating equipment citywide. 2. Survey and report on existing conditions of heating equipment. 3. Assist Heating Superintendent with periodic reports. 4. Assist skill trades staff. 5. Provide assistance during emergencies. 6. Respond to all heating/hot water service disruptions. Candidates selected must be available to work and travel throughout the five boroughs; and will be required to work rotating shifts, including holidays and weekends. 8:00 AM - 4:00 PM 4:00 PM - 12:00 AM 12:00 AM - 8:00 AM
4th rowUnder direct supervision, assist in the routine maintenance operation and repair of public buildings, structures, and the equipment they contain; perform related work. Responsibilities include, but are not limited to the following: 1. Perform minor and major repairs to boilers, burners, vacuum tank, pumps, motors and other various heating equipment citywide. 2. Survey and report on existing conditions of heating equipment. 3. Assist Heating Superintendent with periodic reports. 4. Assist skill trades staff. 5. Provide assistance during emergencies. 6. Respond to all heating/hot water service disruptions. Candidates selected must be available to work and travel throughout the five boroughs; and will be required to work rotating shifts, including holidays and weekends. 8:00 AM - 4:00 PM 4:00 PM - 12:00 AM 12:00 AM - 8:00 AM
5th rowResponsibilities of selected candidates will include, but are not limited to the following: 1. Prepare, fill and prime surfaces for painting. 2. Mix paint components and match colors. 3. Apply paint with a brush, roller or spray gun. 4. Apply plaster to surfaces. 5. Work on and from ladders, platforms and scaffolds 6. Rig lines and scaffolds.

Common Values

ValueCountFrequency (%)
The New York City Taxi and Limousine Commission (TLC) is the agency responsible for regulating New York City's taxicab and for-hire vehicle industry. TLC licenses and regulates over 130,000 vehicles and more than 175,000 drivers, making it the most active taxi and limousine regulatory agency in the United States. Aside from vehicles and drivers, TLC also regulates taxicab agents and for-hire vehicle bases, including popular app-based transportation services. The TLC plays a pivotal role in furthering public safety within New York City and is a lead agency in a citywide effort to reduce traffic-related injuries. One of the largest components of TLC’s operations is the enforcement of agency and administrative code regulations. The Prosecution Division investigates and prosecutes all summonses issued by TLC which consist of administrative, field and consumer-initiated complaints. Our division prosecutes a wide range of violations including reckless driving, unlicensed operation, illegal street pickups, harassment and leaving the scene of an accident. Prosecuting Attorneys represent TLC on cases heard before the Hearings Division of the Office of Administrative Trials and Hearings and will gain robust hands-on litigation experience as they rotate through various prosecutorial assignments, including Consumer Intake, Settlements, Hearings and Appeals. Duties and responsibilities will include, but are not limited to: • Managing a daily caseload and independently representing the Taxi and Limousine Commission at administrative hearings, including preparing and presenting witnesses and evidence at trial. • Evaluating case strengths and weaknesses to effectively negotiate plea and settlement agreements with respondents and/or their attorneys or representatives. • Interviewing consumer complainants to obtain complaint details and determine appropriate charging violations and settlement offers. • Reviewing hearing dispositions for summonses dismissed at OATH; drafting appeals and Chair petitions when appropriate.14
 
0.5%
The New York City Taxi and Limousine Commission (TLC) is the City agency responsible for oversight of the for-hire vehicle industries in New York City, which Include yellow medallion taxis, green Boro taxis, community car services and livery cars, black cars services, luxury limousines, commuter vans and Para-transit services. Combined, TLC regulates Industries that are responsible for over 800,000 daily trips. Our role is to ensure that each passenger's riding experience is safe comfortable and convenient and that TLC drivers are driving safely. Under direction of the Executive leadership of the TLC Uniformed Services Bureau, the Enforcement Deputy Chief will: • Oversee enforcement squads assigned to the overnight shift that conduct patrol and other enforcement operations citywide. • Provide training and mentoring for all rank levels. • Partner with other law enforcement agencies and industry stakeholders when developing enforcement strategies. • Develop and manage a unified approach to addressing illegal for-hire activity, utilizing enforcement statistics to determine performance measures. • Utilize enforcement statistics and for-hire trip data to identify trends that will inform staff deployment and enforcement strategies. • Present at internal and external meetings/briefing on Enforcement Division performance. • Deputy Chief will make changes to deployment strategies and squad assignments ensuring the Enforcement Division capability to carry out its mission and responsibilities in an exemplary manner. • Deputy Chief will be responsible for other management projects and responsibilities as determined by Uniformed Services Bureau Leadership. • Author Division memos related to disciplinary action and unusual incidents; tactical plans and review all written documentation drafted by junior supervisory staff. • Conduct initial internal investigations regarding the behavior of staff in violation of agency policy which may impact employee’s Special Patrolmen status with the NYPD. • Attend community meeting (i.e. precinct community council meetings, town halls, inter-agency operation meetings, etc.). • Inform staff of current directives and orders • Responsible for serviceability, proper care and use of equipment, patrol and administrative record keeping. • Responsible for conducting annual and probationary performance evaluations. • Instruct and frequently test the knowledge of staff regarding their duties and responsibilities. • Be available via agency mobile device 24/7 to senior leadership and direct reports. • Conduct frequent uniform inspections of staff including equipment and general appearance in the field while on patrol. • Review activity of squads assigned daily, monthly, quarterly and annually. • Provide formal orientation for newly promoted and assigned Captains and Lieutenants. • Dotted line oversight over Division Radio Command Operations Desk (aka Central). • Initiate disciplinary process as needed.6
 
0.2%
The NYC Mayor’s Office of Environmental Remediation (OER) designs and implements the City’s brownfield cleanup and redevelopment initiatives. Foremost among these is the NYC Voluntary Cleanup Program (NYC VCP), the nation’s first municipally-run cleanup program, which offers remedial oversight and liability protection to property owners and developers of over 80 sites each year. Brownfields are sites where redevelopment is complicated by the presence of contamination, such as from prior site uses, historic fill, or chemical spills. The office manages the NYC Clean Soil Bank that arranges the reuse of clean soil from deep excavations to provide substantial financial and environmental benefits. OER also supports Community Brownfield Planning Areas and administers the Brownfield Incentive Grant (BIG) program, which provides funding for the investigation and cleanup of brownfield sites as well as grants to community-based organizations conducting planning around brownfields. Additional OER programs and initiatives include the E-Designation Review Program for hazardous materials, air quality, and noise; Green Property Certification; and community engagement activities. To learn more about OER, please visit www.nyc.gov/oer. OER seeks a Project Manager to perform professional scientific work in engineering geology and geology on project sites under the E-Designation and City’s Voluntary Cleanup program. Duties will include but are not limited to: • Implement applicable laws and regulations and policy to meet Mayor’s Office, DEP, and OneNYC strategic environmental, remedial and engineering goals. • Become fluent in all OER Environmental Quality programs (NYC VCP, E-Designation Hazmat, Noise and Air) and other OER Programs including JumpStart, BIG Grants, Brownfield Partnership, Green Team, Green Property Certification, SPEED, EPIC, Clean Soil Bank, PURE Soil NYC and be prepared to provide assistance and answer questions from public. • Review plans, reports and schedules prepared by consultants, contractors, and agencies, and produce engineering analyses to assure technical quality and conformance with project completion dates, as well as with technical, programmatic, and regulatory considerations. • Conduct communications with development teams, the general public, elected officials, the press and other city agencies in accordance with OER, Mayor’s Office and DEP policies. • Oversee, inspect, and participate in field sampling and remediation, and oversee engineering activities. • Maintains databases and archives established by OER management for oversight of programs.4
 
0.1%
The Family Court Division is currently seeking applicants for the position of Assistant Borough Chief (ABC)/RTA Transfer Supervisor in the Division’s Juvenile Delinquency Prosecution Unit. The Family Court Division’s Juvenile Delinquency Prosecution Unit investigates, and prosecutes where appropriate, juvenile delinquency matters involving youth ages 7 to 17 who have been arrested for conduct that would constitute a crime if they were an adult. In accordance with recently enacted Raise the Age legislation, the division also investigates and prosecutes matters involving 16 and 17-year-olds in misdemeanor cases that originate in Family Court and felony cases which begin in the Youth Part of the Superior Court and are transferred to Family Court. The Family Court Division’s Juvenile Delinquency Prosecution Unit seeks to ensure that those youth who commit delinquent acts are held accountable for their misconduct and receive appropriate services. The Family Court system is focused on rehabilitation. The qualified applicants will be assigned to a borough based on borough needs. The primary responsibility of the ABC/RTA Transfer Supervisor will be to supervise and manage the flow of cases originating in the Youth Part. These responsibilities may include, but are not limited to: • Conferring with the District Attorney’s Office in the assigned borough regarding adolescent offender cases for purposes of compiling paperwork on adolescent offender cases and obtaining a copy of their file where a case is being removed/transferred to Family Court; • Conducting court appearances and supervising attorneys on cases being removed/transferred to Family Court when a bridge order of protection is requested; • Preparing, analyzing, and utilizing statistical data with respect to cases originating in the Youth Part; • Supervising support professionals assigned to assist with the flow of cases originating in the Youth Part; • Working and supervising in an overall fast-paced environment. Additional duties in Family Court may include, but are not limited to: • Supervising and training multiple staff attorneys; overseeing their cases from referral through disposition both in and out of the courtroom; • Providing legal and strategic advice to staff attorneys on their cases; • Assisting the Borough Chief, Deputy Borough Chief(s), and Assistant Borough Chief(s) with office initiatives and administrative duties; • Conducting case reviews, transcript reviews, and court observations; • Identifying, recommending, and referring matters for diversion; • Working with victims and advocating on their behalf; • Developing an understanding of New York City communities and the concerns of those who live in them by maintaining a consistent presence in these communities, and collaborating with community stakeholders to prevent and address juvenile delinquency; • Assisting staff attorneys in the identification, recommendation, and negotiation of matters appropriate for plea resolution; • Reviewing and editing written work, including petitions, supporting depositions, motions, and Memoranda of Law; • Reviewing court orders including, but not limited to motion decisions; • Ensuring the accurate data entry of litigation events; • Conducting courtroom observations and providing feedback to staff attorneys; • Assisting with training legal staff and support professionals; • Supervising support professionals; • Maintaining an active caseload; • Preparing, analyzing and utilizing statistical data; • Developing and maintaining collaborative relationships with all Division supervisors; • Writing, reviewing, and editing yearly performance evaluations for staff attorneys and support staff; • Assisting in the development and implementation of borough and Division-wide policies, procedures and protocols; • Representing the Division at interagency committee meetings; • Serving as a liaison to city and statewide agencies including but not limited to the NYPD, the District Attorneys’ Offices, the Department of Probation and the Administration of Children’s Services; • Conducting regular meetings with management or managerial staff, staff attorneys, and support professionals; • Drafting, reviewing, and monitoring performance enhancement and improvement plans. • Participating in a city-wide on-call system for juvenile offenses that take place during evening and weekend hours; • Working on cases and other responsibilities, including visiting crime scenes, in the evening and weekend hours; • Attending community events and meetings, including in the evening and weekend hours. ** This position will periodically involve participation in a citywide rotation of night/weekend court assignments. **4
 
0.1%
The Department of Citywide Administrative Services’ (“DCAS”) Division of Energy Management (“DEM”) serves as the hub for energy management for City government operations. Today, we develop the City’s annual Heat, Light, and Power Budget; manage the City’s electricity, natural gas, and steam accounts; help our agency partners identify and pursue energy-saving opportunities at their buildings; do energy efficiency and clean power generation projects across the City’s portfolio; and implement operations and maintenance (O&M) best practices. DEM is tasked with leading the City’s efforts to reduce greenhouse gas (“GHG”) emissions by 80 percent by 2050 from a 2005 baseline (“80x50”). As part of Local Law 97, the City also recently set new targets to reduce emissions from City government operations by 40 percent by 2025 (“40x25”) and by 50 percent by 2030 (“50x30”). To meet these goals, DEM is committed to collaborating very closely with our agency partners to help them achieve major emissions reductions in their buildings. We actively are working to provide our agency partners with the energy efficiency and clean energy project funding, project delivery vehicles, technical expertise, staff resources, strategic planning support, and data analytics that they need to succeed. DEM seeks to hire a Project Manager, Capital Project Implementation to serve within our Operations Unit. The Project Manager will oversee the implementation of diverse energy efficiency projects. The person’s primary responsibility will be to manage consultants and contractors who are engaged in the design and construction of energy efficiency capital projects at City facilities. With wide latitude for the exercise of independent judgment and initiative, the Project Manager, Capital Project Implementation will be charged with the following responsibilities: • Managing energy efficiency project scoping: Develops and reviews scopes of work for energy efficiency projects, working closely with contractors and consultants. Reviews completed Energy Audits and Energy Efficiency Reports (EERs) for buildings to help guide project selection and alternatives analysis. • Managing the design and construction process for energy efficiency projects: In close collaboration with contractors and consultants, manages the execution of design and construction for a sizable portfolio of energy-related capital projects. Ensures that projects are completed in a timely, cost-effective manner. Reviews, provides comments, and makes recommendations on design packages submitted by consultants for proposed energy efficiency projects. • Performing technical calculations to verify estimated project energy usage, energy cost, and emissions: Performs engineering calculations and energy modeling to verify the reasonableness and accuracy of estimated energy usage reductions, energy cost savings, and avoided greenhouse gas emissions for proposed energy efficiency projects. • Performing site visits throughout the project implementation process: Conducts field visits to assess energy usage reduction opportunities at City buildings; refine proposed scopes of work; facilitate consultants and contractors’ walk-throughs with agency staff; ensure project compliance with the scope and schedule set forth in contract documents; and perform measurement and verification activities. • Conducting measurement and verification activities: Performs measurement and verification tasks to assess realized savings from completed energy efficiency projects. • Coordinating with agency partners, consultants, and contractors: As designated, represents DEM in meetings with different City agencies, consultants, and contractors involved in energy efficiency project implementation. • Performing program data collection, tracking, and reporting: Performs program data collection and tracking required to ensure accurate, on-demand project reporting in a range of areas, including compliance with project schedule, budgets, and scopes; measurement and verification of energy savings and avoided emissions; and projects’ contributions towards the City’s goals. Maintains relevant DEM project tracking databases.4
 
0.1%
The TLC is looking for four responsible College Aides to serve as Outreach Interns. The selected candidates may be responsible for the following tasks: • Translation and Translation Review: We are looking for interns who are fluent in languages in addition to English to assist us with translation and translation review. Our most needed languages include: Spanish, Arabic, Bengali, Chinese, French, Haitian Creole, Korean, Polish, Russian and Urdu • Vision Zero Safety Education: Interns will be responsible for conducting Vision Zero safety education to TLC licensees by visiting FHV bases and taxi garages to give presentations and distribute information about Vision Zero, the mayoral initiative to eliminate pedestrian fatalities. Interns in this department help make NYC streets safer by presenting to TLC licensees about Vision Zero and safe driving principles, having TLC licensed drivers sign the Safe Driving Pledge, and answers any questions TLC licensees may have about Vision Zero. • Outreach on TLC Initiatives: Interns will also be responsible for distribution of TLC outreach materials citywide. This may entail attending events with drivers or passengers, visiting FHV bases and taxi garages, assisting in the development of outreach materials, and meeting with stakeholders. • Lost Property: Interns may be responsible for various tasks involving our Lost Property department. Lost Property receives inquiries from passengers of TLC-licensed vehicles about items they have left in these vehicles, and works to reunite passengers with their lost belongs.4
 
0.1%
The NYC Department of Sanitation is the world’s largest sanitation department. DSNY collects more than 10,500 tons of residential and institutional garbage and 1,760 tons of the recyclables — each day. While efficiently managing solid waste and clearing litter or snow from 6,300 miles of streets, the Department is also a leader in environmentalism — committing to sending zero waste to landfills. The Medical Division consists of an occupational health care facility with a medical staff that monitors the medical condition of more than 8,000 employees. The primary responsibilities of this position are to: • Examine and evaluate the health status of employees who are injured on the job or recovering from an illness to determine their fitness for duty; • May conduct staff meetings, clinical conferences and training programs for the staff; • Works closely with other physicians, nurses, administrative and clerical staff; • Performs other medical specialty assignments equivalent to the typical tasks described above.4
 
0.1%
New York City is home to approximately 1.64 million older adults, and the Department for the Aging (DFTA) is committed to helping them age in their homes and communities. The mission of DFTA is to eliminate ageism and ensure the dignity and quality of life of diverse older adults. DFTA also works to support caregivers through service, advocacy, and education. DFTA seeks a dynamic, motivated and detail-oriented individual to serve as a College Aide, to work in the Office of Information & Technology. The Office of Information & Technology is tasked to lead DFTA’s efforts to ensure that databases are up and running and provide a seamless flow of information throughout the agency considering both back-end data structure and front-end accessibility for end users. The Office of Information & Technology also ensures that DFTA’s computer systems are on par with the advanced technology therefore agency staff can provide services to caregivers and DFTA funded programs. Agency staff computer equipment is always functional and maintained due to Help Desk support which is provided within the agency and throughout DFTA funded programs. In this role, the College Aide will: • Provide in field technical support and assistance for DFTA’s applications to end-users. • Provide in field technical support in a courteous and professional manner. • Provide knowledgeable support for agency developed and third party software. • Fully understand the functional and operational features of agency developed software. • Understanding of the basic functions and features of applications. • Perform the initial setup and/or upgrades to microcomputer equipment and software, and assure their proper operation and connectivity to local area network and Internet. • Troubleshoot issues with hand held bar code scanners and agency printing issues. • Install and update of agency developed and third party software and update virus scan and windows updates as needed. • Diagnose problems on site and provide resolutions. • Assist with training DFTA users with agency software’s.4
 
0.1%
The New York City Department of Housing Preservation and Development (HPD) is the nation’s largest municipal housing preservation and development agency. Its mission is to promote quality housing and diverse, thriving neighborhoods for New Yorkers through loan and development programs for new affordable housing, preservation of the affordability of the existing housing stock, enforcement of housing quality standards, and educational programs for tenants and building owners. HPD is tasked with fulfilling Mayor de Blasio’s Housing New York Plan which was recently expanded and accelerated through Housing New York 2.0 to complete the initial goal of 200,000 homes two years ahead of schedule by 2022, and achieve an additional 100,000 homes over the following four years, for a total of 300,000 homes by 2026. Your Team: The Office of Building and Land Development Services (BLDS) leads the agency’s effort in providing architectural, engineering, environmental planning, and construction support services to the various divisions within HPD’s Office of Development. The Office of Development utilizes a public-private partnership model and provides loans, grants and/or incentives to assist in the finance of housing development projects that will benefit low- and moderate-income New Yorkers. The Division of Building and Land Development Services is the largest division within the Office of Development with over 120 staff composed of seven Unit which include; the Bureau of New Construction Design Services, the Bureau of Preservation Design Services, the Bureau of Engineering, the Bureau of Construction Services, Environmental Planning Unit, the Codes and Standards Unit, and the Program Management Unit. Your Impact: As a Construction Project Manager, you will oversee and monitor the construction activities for projects that are HPD financed projects as part of the Mayor’s Housing New York plan and ensure construction quality and safety at HPD-financed sites. Your Role: The ideal candidate should have a background in Construction Management, Architecture, Engineering, or related field, and possess a thorough understanding and strong knowledge base of New York City building and construction codes, as well as Federal, State, and City housing codes and regulations. Your Responsibilities: • Perform field work and assist in monitoring the construction progress of multiple projects simultaneously and assure work is completed in a cost-effective and timely manner, and in accordance with the approved contract documents and all applicable City, State, and Federal design and construction codes and regulations. • Responsible for performing construction management work and overseeing or assisting in the oversight of the rehabilitation and/or new construction of multi-family projects located within the five boroughs of New York City. • Knowledge of construction contracts and documents, scheduling, site safety, cost and controls. • Perform difficult technical work in determining the need for and feasibility of construction work and monitor private contractors/vendors carrying out new construction, rehabilitation, repairs, alterations, and/or structural maintenance work.4
 
0.1%
Providing technical support to the Affirmative Litigation Division in managing collection matters, referrals and reporting processes for cases. Managing troubleshooting and processing data files into the Law Manager system, interfacing with outside collections and law firms in the monthly process as well as handling new referrals and automation projects. Design and development, testing and implementation, maintenance and enhancement of database management systems, operating systems, data communications and/or computer applications through product lifecycle using MS technology: CRM (2010/2013) and .NET VB / C# (2010/2013). Develop store procedure/SSIS packages, test, install, migrate and applying software and database schema changes, reporting services in regard to SQL 2008/2012. Supporting the testing and implementation of various internal /external NYC LAW data exchange interfaces via SQL, Administer and support MS Team Foundation Server 2013 (TFS) and Crystal Reports.4
 
0.1%
Other values (1598)2894
98.2%

Length

2021-06-21T11:44:00.418187image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
and72297
 
7.1%
the53150
 
5.2%
of34394
 
3.4%
to27458
 
2.7%
in15002
 
1.5%
for14038
 
1.4%
13297
 
1.3%
with11891
 
1.2%
a8969
 
0.9%
as7537
 
0.7%
Other values (13800)760107
74.7%

Most occurring characters

ValueCountFrequency (%)
1040876
14.5%
e668048
 
9.3%
i492841
 
6.9%
t491560
 
6.9%
n485157
 
6.8%
a452500
 
6.3%
o405764
 
5.7%
s386979
 
5.4%
r383130
 
5.4%
l227345
 
3.2%
Other values (100)2123072
29.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5594522
78.2%
Space Separator1040876
 
14.5%
Uppercase Letter293975
 
4.1%
Other Punctuation145571
 
2.0%
Decimal Number32854
 
0.5%
Control12412
 
0.2%
Dash Punctuation11739
 
0.2%
Close Punctuation8779
 
0.1%
Open Punctuation8459
 
0.1%
Final Punctuation6728
 
0.1%
Other values (7)1357
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e668048
11.9%
i492841
 
8.8%
t491560
 
8.8%
n485157
 
8.7%
a452500
 
8.1%
o405764
 
7.3%
s386979
 
6.9%
r383130
 
6.8%
l227345
 
4.1%
d222805
 
4.0%
Other values (19)1378393
24.6%
Uppercase Letter
ValueCountFrequency (%)
C34272
11.7%
T24827
 
8.4%
D23192
 
7.9%
P21822
 
7.4%
S20943
 
7.1%
E20574
 
7.0%
A19900
 
6.8%
O15237
 
5.2%
N14361
 
4.9%
I13829
 
4.7%
Other values (16)85018
28.9%
Other Punctuation
ValueCountFrequency (%)
,63526
43.6%
.40847
28.1%
13972
 
9.6%
;10428
 
7.2%
:5122
 
3.5%
/5064
 
3.5%
*2750
 
1.9%
'1598
 
1.1%
&1498
 
1.0%
#281
 
0.2%
Other values (9)485
 
0.3%
Decimal Number
ValueCountFrequency (%)
011153
33.9%
16685
20.3%
23525
 
10.7%
52822
 
8.6%
32305
 
7.0%
61635
 
5.0%
41416
 
4.3%
81404
 
4.3%
91011
 
3.1%
7898
 
2.7%
Open Punctuation
ValueCountFrequency (%)
(8444
99.8%
[11
 
0.1%
{4
 
< 0.1%
Close Punctuation
ValueCountFrequency (%)
)8762
99.8%
]13
 
0.1%
}4
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
-11318
96.4%
315
 
2.7%
106
 
0.9%
Math Symbol
ValueCountFrequency (%)
+87
57.6%
~44
29.1%
>20
 
13.2%
Final Punctuation
ValueCountFrequency (%)
6348
94.4%
380
 
5.6%
Control
ValueCountFrequency (%)
12379
99.7%
33
 
0.3%
Initial Punctuation
ValueCountFrequency (%)
370
97.6%
9
 
2.4%
Currency Symbol
ValueCountFrequency (%)
$677
99.7%
2
 
0.3%
Other Symbol
ValueCountFrequency (%)
¦18
56.2%
°14
43.8%
Space Separator
ValueCountFrequency (%)
1040876
100.0%
Format
ValueCountFrequency (%)
­2
100.0%
Connector Punctuation
ValueCountFrequency (%)
_112
100.0%
Other Number
ValueCountFrequency (%)
½2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin5888497
82.3%
Common1268775
 
17.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e668048
 
11.3%
i492841
 
8.4%
t491560
 
8.3%
n485157
 
8.2%
a452500
 
7.7%
o405764
 
6.9%
s386979
 
6.6%
r383130
 
6.5%
l227345
 
3.9%
d222805
 
3.8%
Other values (45)1672368
28.4%
Common
ValueCountFrequency (%)
1040876
82.0%
,63526
 
5.0%
.40847
 
3.2%
13972
 
1.1%
12379
 
1.0%
-11318
 
0.9%
011153
 
0.9%
;10428
 
0.8%
)8762
 
0.7%
(8444
 
0.7%
Other values (45)47070
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII7135414
99.7%
Punctuation21502
 
0.3%
Latin 1 Sup354
 
< 0.1%
Currency Symbols2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1040876
14.6%
e668048
 
9.4%
i492841
 
6.9%
t491560
 
6.9%
n485157
 
6.8%
a452500
 
6.3%
o405764
 
5.7%
s386979
 
5.4%
r383130
 
5.4%
l227345
 
3.2%
Other values (81)2101214
29.4%
Punctuation
ValueCountFrequency (%)
13972
65.0%
6348
29.5%
380
 
1.8%
370
 
1.7%
315
 
1.5%
106
 
0.5%
9
 
< 0.1%
2
 
< 0.1%
Latin 1 Sup
ValueCountFrequency (%)
¿190
53.7%
§78
22.0%
·41
 
11.6%
¦18
 
5.1%
°14
 
4.0%
ç5
 
1.4%
­2
 
0.6%
½2
 
0.6%
â2
 
0.6%
à2
 
0.6%
Currency Symbols
ValueCountFrequency (%)
2
100.0%

Minimum Qual Requirements
Categorical

HIGH CARDINALITY

Distinct336
Distinct (%)11.5%
Missing20
Missing (%)0.7%
Memory size23.1 KiB
1. A baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2. High school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least one year of experience as described in "1" above.
 
182
1. Admission to the New York State Bar; and either "2" or "3" below. 2. One year of satisfactory United States legal experience subsequent to admission to any state bar; or 3. Six months of satisfactory service as an Agency Attorney Interne (30086). Incumbents must remain Members of the New York State Bar in good standing for the duration of this employment. In addition to meeting the minimum Qualification Requirements: To be assigned to Assignment Level (AL) II, candidates must have one year of experience at Assignment Level I or two years of comparable legal experience subsequent to admission to the bar, in the areas of law related to the assignment. To be assigned to AL III candidates must have two years of experience in Assignment Levels I and/or II or three years of comparable legal experience subsequent to admission to the bar, in the areas of law related to the assignment.
 
112
(1) Four (4) years of full-time, satisfactory experience in civil engineering work; and (2) A valid New York State Professional Engineer’s License. Current New York State registration as a Professional Engineer must be maintained for the duration of your employment. A masters degree in civil engineering from an accredited college or university, accredited by regional, national, professional or specialized agencies recognized as accrediting bodies by the U.S. Secretary of Education and by the Council for Higher Education Accreditation (CHEA) may be substituted for one year of the civil engineering experience required in “1" above. Special Note: In addition to above qualification requirements, to be eligible for placement in Assignment Levels II and III, individuals must have at least one year within the last three years of experience as a major contributor or a project leader on a complex project requiring additional and specific expertise in the disciplines needed to design or construct the project.
 
87
1. For Assignment Level I (only physical, biological and environmental sciences and public health) A master's degree from an accredited college or university with a specialization in an appropriate field of physical, biological or environmental science or in public health. To be appointed to Assignment Level II and above, candidates must have: 1. A doctorate degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and one year of full-time experience in a responsible supervisory, administrative or research capacity in the appropriate field of specialization; or 2. A master's degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and three years of responsible full-time research experience in the appropriate field of specialization; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least a master's degree in an appropriate field of specialization and at least two years of experience described in "2" above. Two years as a City Research Scientist Level I can be substituted for the experience required in "1" and "2" above. NOTE: Probationary Period Appointments to this position are subject to a minimum probationary period of one year.
 
83
1. A four-year high school diploma or its educational equivalent approved by a State’s Department of Education or a recognized accrediting organization, and five years of full-time satisfactory experience managing and/or inspecting one or more construction projects which must have a total cost of at least $300,000 for each of the five years of the required experience; or 2. One year of the experience as described in “1” above and a baccalaureate degree from an accredited college or university, accredited by regional, national, professional or specialized agencies recognized as accrediting bodies by the U. S. Secretary of Education and by the Council for Higher Education Accreditation (CHEA), in engineering, engineering technology, architecture, architectural technology, landscape architecture, construction, construction technology, or construction management; or 3. One year of the experience as described in “1” above and a valid license as a professional engineer, registered architect, or registered landscape architect, issued by a board of examining engineers, architects, or landscape architects duly established and qualified pursuant to the laws of any state or territory of the United States; or 4. A four-year high school diploma or its educational equivalent approved by a State's Department of Education or a recognized accrediting organization, and a combination of at least two years of experience as described in “1” above and the education as described in “2” above to equal a total of five years of education and experience. Matriculation in an undergraduate college degree program as described in “2” above may be substituted for experience on the basis of 30 semester credits for one year of satisfactory full-time experience up to a maximum of three years of experience. Note: Candidates must specify for each construction project they worked on: a description of the construction project, the time period they worked on the construction project, and the type of work they performed. Candidates must also specify the money allotted for the project. Driver License Requirement: At the time of appointment to this position, you must have a motor vehicle driver license valid in the State of New York. If you have moving violations, license suspension or an accident record, you may be disqualified. This license must be maintained for the duration of your employment. 5. For Assignment to Level II, In addition to meeting the "Qualification Requirements" above, candidates must have one additional year of satisfactory full-time experience working in Assignment Level I; or one additional year of satisfactory full-time experience as described in "1" above. 6. For Assignment to Level III, in addition to meeting the Qualification Requirements for Construction Project Manager, candidates must have two additional years of satisfactory full-time experience working in Construction Project Manager Assignment Level I and II; or two additional years of satisfactory full-time experience as described in question "1" above and possess a motor vehicle driver license valid in the State of New York which must be maintained for the duration of employment noting that if you have moving violations, license suspension or an accident record, you may be disqualified.
 
72
Other values (331)
2390 

Length

Max length4310
Median length954
Mean length1104.586808
Min length50

Characters and Unicode

Total characters3232021
Distinct characters82
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)1.0%

Sample

1st row1. A baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2. High school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least one year of experience as described in "1" above.
2nd row1. A baccalaureate degree from an accredited college or university and five years of full-time paid experience acquired within the last fifteen years, of supervisory or administrative experience including handling of business promotion or urban economic problems, at least 2 years of which must have been in a managerial or executive capacity with primary focus on business promotion or urban economic planning; or 2. A satisfactory equivalent combination of education and experience. However all candidates must have 2 years of managerial or executive experience as described in "1" above. Appropriate graduate study in an accredited college or university may be substituted for the general experience on a year-for-year basis. All candidates must have a four-year high school diploma or its equivalent approved by a State's Department of Education or a recognized accrediting organization.
3rd row1. Three years of full-time satisfactory experience as a mechanic, journey person or helper in the electrical trades, the mechanical trades, or the construction or maintenance of buildings; or 2. A satisfactory combination of education and experience that is equivalent to "1" above. Education may be substituted for experience on the basis that each one year of full-time training in the electrical, mechanical, or construction trades in a trade school or vocational high school approved by a State’s Department of Education or a recognized accrediting organization, may be substituted for six months of the experience described in "1" above. However, all candidates must have a minimum of two years of experience as described in "1" above.
4th row1. Three years of full-time satisfactory experience as a mechanic, journey person or helper in the electrical trades, the mechanical trades, or the construction or maintenance of buildings; or 2. A satisfactory combination of education and experience that is equivalent to "1" above. Education may be substituted for experience on the basis that each one year of full-time training in the electrical, mechanical, or construction trades in a trade school or vocational high school approved by a State’s Department of Education or a recognized accrediting organization, may be substituted for six months of the experience described in "1" above. However, all candidates must have a minimum of two years of experience as described in "1" above.
5th row1. Five years of full-time satisfactory experience as a painter acquired within the last fifteen years; or 2. At least three years of full-time satisfactory experience as a painter acquired within the last fifteen years and sufficient full-time satisfactory apprentice painter experience to make up a total of five years of acceptable experience. Six months of acceptable experience will be credited for each year of apprentice painter experience.

Common Values

ValueCountFrequency (%)
1. A baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2. High school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least one year of experience as described in "1" above.182
 
6.2%
1. Admission to the New York State Bar; and either "2" or "3" below. 2. One year of satisfactory United States legal experience subsequent to admission to any state bar; or 3. Six months of satisfactory service as an Agency Attorney Interne (30086). Incumbents must remain Members of the New York State Bar in good standing for the duration of this employment. In addition to meeting the minimum Qualification Requirements: To be assigned to Assignment Level (AL) II, candidates must have one year of experience at Assignment Level I or two years of comparable legal experience subsequent to admission to the bar, in the areas of law related to the assignment. To be assigned to AL III candidates must have two years of experience in Assignment Levels I and/or II or three years of comparable legal experience subsequent to admission to the bar, in the areas of law related to the assignment.112
 
3.8%
(1) Four (4) years of full-time, satisfactory experience in civil engineering work; and (2) A valid New York State Professional Engineer’s License. Current New York State registration as a Professional Engineer must be maintained for the duration of your employment. A masters degree in civil engineering from an accredited college or university, accredited by regional, national, professional or specialized agencies recognized as accrediting bodies by the U.S. Secretary of Education and by the Council for Higher Education Accreditation (CHEA) may be substituted for one year of the civil engineering experience required in “1" above. Special Note: In addition to above qualification requirements, to be eligible for placement in Assignment Levels II and III, individuals must have at least one year within the last three years of experience as a major contributor or a project leader on a complex project requiring additional and specific expertise in the disciplines needed to design or construct the project.87
 
3.0%
1. For Assignment Level I (only physical, biological and environmental sciences and public health) A master's degree from an accredited college or university with a specialization in an appropriate field of physical, biological or environmental science or in public health. To be appointed to Assignment Level II and above, candidates must have: 1. A doctorate degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and one year of full-time experience in a responsible supervisory, administrative or research capacity in the appropriate field of specialization; or 2. A master's degree from an accredited college or university with specialization in an appropriate field of physical, biological, environmental or social science and three years of responsible full-time research experience in the appropriate field of specialization; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least a master's degree in an appropriate field of specialization and at least two years of experience described in "2" above. Two years as a City Research Scientist Level I can be substituted for the experience required in "1" and "2" above. NOTE: Probationary Period Appointments to this position are subject to a minimum probationary period of one year.83
 
2.8%
1. A four-year high school diploma or its educational equivalent approved by a State’s Department of Education or a recognized accrediting organization, and five years of full-time satisfactory experience managing and/or inspecting one or more construction projects which must have a total cost of at least $300,000 for each of the five years of the required experience; or 2. One year of the experience as described in “1” above and a baccalaureate degree from an accredited college or university, accredited by regional, national, professional or specialized agencies recognized as accrediting bodies by the U. S. Secretary of Education and by the Council for Higher Education Accreditation (CHEA), in engineering, engineering technology, architecture, architectural technology, landscape architecture, construction, construction technology, or construction management; or 3. One year of the experience as described in “1” above and a valid license as a professional engineer, registered architect, or registered landscape architect, issued by a board of examining engineers, architects, or landscape architects duly established and qualified pursuant to the laws of any state or territory of the United States; or 4. A four-year high school diploma or its educational equivalent approved by a State's Department of Education or a recognized accrediting organization, and a combination of at least two years of experience as described in “1” above and the education as described in “2” above to equal a total of five years of education and experience. Matriculation in an undergraduate college degree program as described in “2” above may be substituted for experience on the basis of 30 semester credits for one year of satisfactory full-time experience up to a maximum of three years of experience. Note: Candidates must specify for each construction project they worked on: a description of the construction project, the time period they worked on the construction project, and the type of work they performed. Candidates must also specify the money allotted for the project. Driver License Requirement: At the time of appointment to this position, you must have a motor vehicle driver license valid in the State of New York. If you have moving violations, license suspension or an accident record, you may be disqualified. This license must be maintained for the duration of your employment. 5. For Assignment to Level II, In addition to meeting the "Qualification Requirements" above, candidates must have one additional year of satisfactory full-time experience working in Assignment Level I; or one additional year of satisfactory full-time experience as described in "1" above. 6. For Assignment to Level III, in addition to meeting the Qualification Requirements for Construction Project Manager, candidates must have two additional years of satisfactory full-time experience working in Construction Project Manager Assignment Level I and II; or two additional years of satisfactory full-time experience as described in question "1" above and possess a motor vehicle driver license valid in the State of New York which must be maintained for the duration of employment noting that if you have moving violations, license suspension or an accident record, you may be disqualified.72
 
2.4%
Qualification Requirements A four-year high school diploma or its educational equivalent approved by a State's department of education or a recognized accrediting organization and one year of satisfactory clerical experience. Skills Requirement Keyboard familiarity with the ability to type at a minimum of 100 key strokes (20 words) per minute.72
 
2.4%
Qualification Requirements 1. High school graduation or equivalent and three years of experience in community work or community centered activities in an area related to duties described above; or 2. Education and/or experience which is equivalent to "1" above.69
 
2.3%
1. A master's degree in computer science from an accredited college and three years of progressively more responsible, full-time, satisfactory experience using information technology in computer applications programming, systems programming, computer systems development, data telecommunications, database administration, planning of data/information processing, user services, or area networks at least 18 months of this experience must have been in an administrative, managerial or executive capacity in the areas of computer applications programming, systems programming, computer systems development, data telecommunications, data base administration, or planning of data processing or in the supervision of staff performing these duties; or 2. A baccalaureate degree from an accredited college and four years of experience as described in "1" above; or 3. A four-year high school diploma or its educational equivalent approved by a State's department of education or recognized accrediting organization and six years of experience as described in "1" above; or 4. A satisfactory combination of education and experience equivalent to "1", "2" or "3" above. However, all candidates must have at least a four-year high school diploma or its educational equivalent approved by a State's department of education or recognized accrediting organization and must possess at least three years of experience as described in "1" above, including the 18 months of administrative, managerial, executive or supervisory experience as described in "1" above. Qualification Requirements (continued) NOTE: The following types of experience are not acceptable: superficial use of preprogrammed software without complex programming, design, implementation or management of the product; use of word processing packages; use of a hand held calculator; primarily the entering or updating of data in a system; the operation of data processing hardware or consoles.57
 
1.9%
1. A baccalaureate degree from an accredited college.56
 
1.9%
1. A baccalaureate degree from an accredited college and three years of satisfactory full-time progressively responsible clerical/administrative experience, one year of which must have been in an administrative capacity or supervising staff performing clerical/administrative work of more than moderate difficulty; or 2. An associate degree or 60 semester credits from an accredited college and four years of satisfactory full-time progressively responsible clerical/administrative experience including one year of the administrative supervisory experience described in "1" above; or 3. A four-year high school diploma or its educational equivalent approved by a State's department of education or a recognized accrediting organization and five years of satisfactory full-time progressively responsible clerical/administrative experience including one year of the administrative supervisory experience as described in "1" above; 4. Education and/or experience equivalent to "1", "2", or "3" above. However, all candidates must possess the one year of administrative or supervisory experience as described in "1" above. Education above the high school level may be substituted for the general clerical/administrative experience (but not for the one year of administrative or supervisory experience described in "1" above) at a rate of 30 semester credits from an accredited college for 6 months of experience up to a maximum of 3½ years.53
 
1.8%
Other values (326)2083
70.7%

Length

2021-06-21T11:44:00.778552image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
of22899
 
4.8%
or22755
 
4.8%
in17851
 
3.8%
a15727
 
3.3%
the14210
 
3.0%
experience13118
 
2.8%
and9266
 
1.9%
to8376
 
1.8%
an7110
 
1.5%
years6883
 
1.4%
Other values (2163)337645
71.0%

Most occurring characters

ValueCountFrequency (%)
495681
15.3%
e348850
 
10.8%
i227372
 
7.0%
a224541
 
6.9%
o198151
 
6.1%
n193961
 
6.0%
t192339
 
6.0%
r186185
 
5.8%
s138324
 
4.3%
c128839
 
4.0%
Other values (72)897778
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter2557340
79.1%
Space Separator495681
 
15.3%
Other Punctuation75579
 
2.3%
Uppercase Letter60958
 
1.9%
Decimal Number23836
 
0.7%
Dash Punctuation6246
 
0.2%
Close Punctuation4037
 
0.1%
Open Punctuation3878
 
0.1%
Final Punctuation2151
 
0.1%
Initial Punctuation1811
 
0.1%
Other values (4)504
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e348850
13.6%
i227372
 
8.9%
a224541
 
8.8%
o198151
 
7.7%
n193961
 
7.6%
t192339
 
7.5%
r186185
 
7.3%
s138324
 
5.4%
c128839
 
5.0%
l99115
 
3.9%
Other values (16)619663
24.2%
Uppercase Letter
ValueCountFrequency (%)
A11749
19.3%
I7367
12.1%
S5795
9.5%
E5184
8.5%
L4148
 
6.8%
C3262
 
5.4%
N2938
 
4.8%
T2842
 
4.7%
H2794
 
4.6%
R2023
 
3.3%
Other values (15)12856
21.1%
Decimal Number
ValueCountFrequency (%)
18663
36.3%
25574
23.4%
33096
 
13.0%
02588
 
10.9%
41209
 
5.1%
61103
 
4.6%
8816
 
3.4%
5550
 
2.3%
9160
 
0.7%
777
 
0.3%
Other Punctuation
ValueCountFrequency (%)
,31664
41.9%
.18789
24.9%
"11589
 
15.3%
;6548
 
8.7%
/3457
 
4.6%
:2169
 
2.9%
'1247
 
1.6%
*63
 
0.1%
53
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
-6208
99.4%
38
 
0.6%
Final Punctuation
ValueCountFrequency (%)
1393
64.8%
758
35.2%
Control
ValueCountFrequency (%)
213
100.0%
Space Separator
ValueCountFrequency (%)
495681
100.0%
Initial Punctuation
ValueCountFrequency (%)
1811
100.0%
Open Punctuation
ValueCountFrequency (%)
(3878
100.0%
Close Punctuation
ValueCountFrequency (%)
)4037
100.0%
Other Number
ValueCountFrequency (%)
½79
100.0%
Math Symbol
ValueCountFrequency (%)
+4
100.0%
Currency Symbol
ValueCountFrequency (%)
$208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin2618298
81.0%
Common613723
 
19.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e348850
13.3%
i227372
 
8.7%
a224541
 
8.6%
o198151
 
7.6%
n193961
 
7.4%
t192339
 
7.3%
r186185
 
7.1%
s138324
 
5.3%
c128839
 
4.9%
l99115
 
3.8%
Other values (41)680621
26.0%
Common
ValueCountFrequency (%)
495681
80.8%
,31664
 
5.2%
.18789
 
3.1%
"11589
 
1.9%
18663
 
1.4%
;6548
 
1.1%
-6208
 
1.0%
25574
 
0.9%
)4037
 
0.7%
(3878
 
0.6%
Other values (21)21092
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII3227889
99.9%
Punctuation4053
 
0.1%
Latin 1 Sup79
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
495681
15.4%
e348850
 
10.8%
i227372
 
7.0%
a224541
 
7.0%
o198151
 
6.1%
n193961
 
6.0%
t192339
 
6.0%
r186185
 
5.8%
s138324
 
4.3%
c128839
 
4.0%
Other values (66)893646
27.7%
Punctuation
ValueCountFrequency (%)
1811
44.7%
1393
34.4%
758
18.7%
53
 
1.3%
38
 
0.9%
Latin 1 Sup
ValueCountFrequency (%)
½79
100.0%

Preferred Skills
Categorical

HIGH CARDINALITY
MISSING

Distinct1282
Distinct (%)50.2%
Missing393
Missing (%)13.3%
Memory size23.1 KiB
ERROR: #NAME?
 
41
Interested candidates should have excellent written and verbal communication skills, effective problem-solving skills, and the ability to prioritize, manage time, and engage in multiple tasks in a fast-paced environment. Although not required, the successful applicant will likely have one or more of the following academic or professional experiences: litigation, and/or customer relations. Bilingual proficiency preferred.
 
18
Ability to communicate effectively in verbal and written form.
 
13
1. Knowledge of Microsoft Word, Excel, Outlook, Access and PowerPoint. 2. Office experience as well as demonstrable background dealing with members of the public. 3. Excellent oral and written communication skills. 4. History of volunteerism, such as service in the AmericCorps or Peace Corps, is viewed favorably.
 
12
1. Experience with public housing. 2. Experience performing lead-based paint correction and remediation work for public or private large landlord or contractor. 3. Experience using wireless handheld computer devices to record data. 4. Basic computer skills; experience using Microsoft Outlook.
 
8
Other values (1277)
2461 

Length

Max length2932
Median length509
Mean length611.0842146
Min length9

Characters and Unicode

Total characters1560098
Distinct characters101
Distinct categories15 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique278 ?
Unique (%)10.9%

Sample

1st row• Excellent interpersonal and organizational skills. • Excellent analytic and operational skills. • Excellent writing and editing skills. • Knowledge of government procurement processes and information systems desirable. • Foreign language skills a plus.
2nd row1. A High School Diploma or GED. 2. CDL Driver's License. 3. Excellent trouble-shooting ability and mechanical aptitude. 4. Excellent analytical and organizational skills. 5. Ability to trouble-shoot various types of vacuum heating equipment. 6. Knowledge of steam and pneumatic heating systems; steam and hot water generating systems; various types of heat, air and water pumps. 7. Knowledge of Maximo work order system.
3rd row1. A High School Diploma or GED. 2. CDL Driver's License. 3. Excellent trouble-shooting ability and mechanical aptitude. 4. Excellent analytical and organizational skills. 5. Ability to trouble-shoot various types of vacuum heating equipment. 6. Knowledge of steam and pneumatic heating systems; steam and hot water generating systems; various types of heat, air and water pumps. 7. Knowledge of Maximo work order system.
4th rowStrong analytical background; advanced proficiency in Microsoft Excel and Word; experience in procurement, budget and grant management; understanding of contract management; Strong organizational and administrative skills; and excellent oral, inter-personal and written communication skills.
5th rowIn order to apply for this position, the candidate must be a permanent Associate Chemist or on an Associate Chemist Civil Service List. Experience in testing drinking water samples for trace organic contaminants by EPA-approved gas chromatographic methods is preferred: experience in testing environmental water samples for trace organic contaminants by gas chromatographic methods is also acceptable. Strong writing and communication skills are desirable as well as familiarity with computer programs, including Excel and Word.

Common Values

ValueCountFrequency (%)
ERROR: #NAME?41
 
1.4%
Interested candidates should have excellent written and verbal communication skills, effective problem-solving skills, and the ability to prioritize, manage time, and engage in multiple tasks in a fast-paced environment. Although not required, the successful applicant will likely have one or more of the following academic or professional experiences: litigation, and/or customer relations. Bilingual proficiency preferred.18
 
0.6%
Ability to communicate effectively in verbal and written form.13
 
0.4%
1. Knowledge of Microsoft Word, Excel, Outlook, Access and PowerPoint. 2. Office experience as well as demonstrable background dealing with members of the public. 3. Excellent oral and written communication skills. 4. History of volunteerism, such as service in the AmericCorps or Peace Corps, is viewed favorably.12
 
0.4%
1. Experience with public housing. 2. Experience performing lead-based paint correction and remediation work for public or private large landlord or contractor. 3. Experience using wireless handheld computer devices to record data. 4. Basic computer skills; experience using Microsoft Outlook.8
 
0.3%
A valid NYS Driver's License is required for this position.8
 
0.3%
• At least five years of litigation experience in anti-discrimination law, employment law, housing law, or other civil rights-related areas. • Experience conducting discovery, reviewing documents and taking deposition or trial testimony. • Strong relationships with organizations and groups serving diverse communities in the City and five years’ experience working with some of the following people and communities: low-income tenants, recipients of public assistance, immigrants; people of color; people with limited English proficiency; people living with HIV/AIDS; lesbian, gay, bisexual and/or transgender people; people with disabilities; people with accommodations issues related to pregnancy, disability or religion; and people with criminal or arrest histories. • Demonstrated commitment to public service and strong work ethic. • Exceptional organization skills and attention to detail • Strong oral and communication skills. • Strong people skills and leadership skills. • Experience working as part of a team and ability to work collaboratively. • Ability to engage with diverse members of the public in a culturally competent manner. • Familiarity with the NYCHRL. • Fluency in a language other than English, preferably one common in New York City.8
 
0.3%
• Excellent oral and written communication skills towards a technical and non-technical audience • Excellent organizational and analytical skills • Excellent interpersonal and team skills • Advanced proficiency in Microsoft Excel • Prior project management and/or engineering coursework or experience a plus • Ability to manage multiple tasks and experience working and managing through complex systems8
 
0.3%
Experience working with distributed computing paradigms, experience in front end development with Javascript, and fluency in other programming languages, such as Scala, R, etc., are highly desirable. Very strong preference given to candidates demonstrating strong creative and analytical problem-solving skills and having experience or demonstrated interest in transportation dynamics, transportation policy, bike share, micromobility, and/or cycling. Experience working with the public, community groups, and New York City agencies, and strong verbal and written communication skills all desired.7
 
0.2%
Candidates must have a Motor Vehicle Driver License valid in the State of New York.6
 
0.2%
Other values (1272)2424
82.3%
(Missing)393
 
13.3%

Length

2021-06-21T11:44:01.204915image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
and15020
 
7.0%
8279
 
3.8%
to6034
 
2.8%
of5869
 
2.7%
in5078
 
2.4%
experience4305
 
2.0%
skills3926
 
1.8%
with3845
 
1.8%
the3748
 
1.7%
a3643
 
1.7%
Other values (6171)155866
72.3%

Most occurring characters

ValueCountFrequency (%)
216346
13.9%
e143878
 
9.2%
i115684
 
7.4%
n109354
 
7.0%
t98820
 
6.3%
a95811
 
6.1%
o84116
 
5.4%
r79494
 
5.1%
s73495
 
4.7%
l64685
 
4.1%
Other values (91)478415
30.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter1215097
77.9%
Space Separator216346
 
13.9%
Uppercase Letter61476
 
3.9%
Other Punctuation45265
 
2.9%
Control7885
 
0.5%
Decimal Number6305
 
0.4%
Dash Punctuation3272
 
0.2%
Close Punctuation1757
 
0.1%
Open Punctuation1541
 
0.1%
Final Punctuation646
 
< 0.1%
Other values (5)508
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e143878
11.8%
i115684
 
9.5%
n109354
 
9.0%
t98820
 
8.1%
a95811
 
7.9%
o84116
 
6.9%
r79494
 
6.5%
s73495
 
6.0%
l64685
 
5.3%
c52649
 
4.3%
Other values (18)297111
24.5%
Uppercase Letter
ValueCountFrequency (%)
S7735
12.6%
E6758
11.0%
A6590
 
10.7%
P4869
 
7.9%
C4842
 
7.9%
M3951
 
6.4%
D2822
 
4.6%
I2497
 
4.1%
T2385
 
3.9%
N2305
 
3.7%
Other values (17)16722
27.2%
Other Punctuation
ValueCountFrequency (%)
,16508
36.5%
.12248
27.1%
8988
19.9%
;3678
 
8.1%
/1715
 
3.8%
:936
 
2.1%
*242
 
0.5%
'200
 
0.4%
¿161
 
0.4%
·158
 
0.3%
Other values (6)431
 
1.0%
Decimal Number
ValueCountFrequency (%)
11147
18.2%
21103
17.5%
3868
13.8%
0789
12.5%
5688
10.9%
4545
8.6%
6369
 
5.9%
7323
 
5.1%
8292
 
4.6%
9181
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
-3208
98.0%
62
 
1.9%
2
 
0.1%
Currency Symbol
ValueCountFrequency (%)
$19
82.6%
2
 
8.7%
¢2
 
8.7%
Control
ValueCountFrequency (%)
7883
> 99.9%
2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
+297
98.7%
>4
 
1.3%
Open Punctuation
ValueCountFrequency (%)
(1537
99.7%
[4
 
0.3%
Close Punctuation
ValueCountFrequency (%)
)1753
99.8%
]4
 
0.2%
Final Punctuation
ValueCountFrequency (%)
624
96.6%
22
 
3.4%
Space Separator
ValueCountFrequency (%)
216346
100.0%
Initial Punctuation
ValueCountFrequency (%)
20
100.0%
Connector Punctuation
ValueCountFrequency (%)
_162
100.0%
Other Symbol
ValueCountFrequency (%)
¦2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1276573
81.8%
Common283525
 
18.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e143878
11.3%
i115684
 
9.1%
n109354
 
8.6%
t98820
 
7.7%
a95811
 
7.5%
o84116
 
6.6%
r79494
 
6.2%
s73495
 
5.8%
l64685
 
5.1%
c52649
 
4.1%
Other values (45)358587
28.1%
Common
ValueCountFrequency (%)
216346
76.3%
,16508
 
5.8%
.12248
 
4.3%
8988
 
3.2%
7883
 
2.8%
;3678
 
1.3%
-3208
 
1.1%
)1753
 
0.6%
/1715
 
0.6%
(1537
 
0.5%
Other values (36)9661
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1550029
99.4%
Punctuation9718
 
0.6%
Latin 1 Sup349
 
< 0.1%
Currency Symbols2
 
< 0.1%

Most frequent character per block

Punctuation
ValueCountFrequency (%)
8988
92.5%
624
 
6.4%
62
 
0.6%
22
 
0.2%
20
 
0.2%
2
 
< 0.1%
ASCII
ValueCountFrequency (%)
216346
14.0%
e143878
 
9.3%
i115684
 
7.5%
n109354
 
7.1%
t98820
 
6.4%
a95811
 
6.2%
o84116
 
5.4%
r79494
 
5.1%
s73495
 
4.7%
l64685
 
4.2%
Other values (76)468346
30.2%
Latin 1 Sup
ValueCountFrequency (%)
¿161
46.1%
·158
45.3%
Â20
 
5.7%
â2
 
0.6%
¢2
 
0.6%
¦2
 
0.6%
§2
 
0.6%
ç2
 
0.6%
Currency Symbols
ValueCountFrequency (%)
2
100.0%

Additional Information
Categorical

HIGH CARDINALITY
MISSING

Distinct681
Distinct (%)36.7%
Missing1092
Missing (%)37.1%
Memory size23.1 KiB
Appointments are subject to OMB approval. For additional information about DEP, visit www.nyc.gov/dep DEP is an equal opportunity employer with a strong commitment to the diversity of our organization and workforce. Your voluntary response to the NYCAPS on-line application section for referral information will assist us tremendously in our ability to track the success of our outreach and recruitment efforts. Please be sure to indicate your source of referral to this job. NOTE: This position is open to qualified persons with a disability who are eligible for the 55-a Program and also meet the education and experience requirements as listed in the job posting notice. Please indicate on your resume or cover letter that you would like to be considered for the position under the 55-a Program. This position is also open to non 55-a Program candidates who meet the education and experience requirements as listed in the job posting notice.
 
87
NYCHA employees applying for promotional, title or level change opportunities must have served a period of one year in their current title and level (if applicable).
 
56
**IMPORTANT NOTES TO ALL CANDIDATES: Please note: If you are called for an interview you will be required to bring to your interview copies of original documentation, such as: • A document that establishes identity for employment eligibility, such as: A Valid U.S. Passport, Permanent Resident Card/Green Card, or Driver’s license. • Proof of Education according to the education requirements of the civil service title. • Current Resume • Proof of Address/NYC Residency dated within the last 60 days, such as: Recent Utility Bill (i.e. Telephone, Cable, Mobile Phone) Additional documentation may be required to evaluate your qualification as outlined in this posting’s “Minimum Qualification Requirements” section. Examples of additional documentation may be, but not limited to: college transcript, experience verification or professional trade licenses. If after your interview you are the selected candidate you will be contacted to schedule an on-boarding appointment. By the time of this appointment you will be asked to produce the originals of the above documents along with your original Social Security card. **LOAN FORGIVENESS The federal government provides student loan forgiveness through its Public Service Loan Forgiveness Program (PSLF) to all qualifying public service employees. Working with the DOHMH qualifies you as a public service employee and you may be able to take advantage of this program while working full-time and meeting the program’s other requirements. Please visit the Public Service Loan Forgiveness Program site to view the eligibility requirements: https://studentaid.ed.gov/sa/repay-loans/forgiveness-cancellation/public-service "FINAL APPOINTMENTS ARE SUBJECT TO OFFICE OF MANAGEMENT & BUDGET APPROVAL”
 
49
**IMPORTANT NOTES TO ALL CANDIDATES: Please note: If you are called for an interview you will be required to bring to your interview copies of original documentation, such as: • A document that establishes identity for employment eligibility, such as: A Valid U.S. Passport, Permanent Resident Card/Green Card, or Driver’s license. • Proof of Education according to the education requirements of the civil service title. • Current Resume • Proof of Address/NYC Residency dated within the last 60 days, such as: Recent Utility Bill (i.e. Telephone, Cable, Mobile Phone) Additional documentation may be required to evaluate your qualification as outlined in this posting’s “Minimum Qualification Requirements” section. Examples of additional documentation may be, but not limited to: college transcript, experience verification or professional trade licenses. If after your interview you are the selected candidate you will be contacted to schedule an on-boarding appointment. By the time of this appointment you will be asked to produce the originals of the above documents along with your original Social Security card. **LOAN FORGIVENESS The federal government provides student loan forgiveness through its Public Service Loan Forgiveness Program (PSLF) to all qualifying public service employees. Working with the DOHMH qualifies you as a public service employee and you may be able to take advantage of this program while working full-time and meeting the program’s other requirements. Please visit the Public Service Loan Forgiveness Program site to view the eligibility requirements: https://studentaid.ed.gov/sa/repay-loans/forgiveness-cancellation/public-service
 
36
Note: This position is open to qualified persons with a disability who are eligible for the 55-a program. Please indicate in your resume or cover letter that you would like to be considered for the position under the 55-a program.
 
35
Other values (676)
1591 

Length

Max length2779
Median length511
Mean length669.3290183
Min length3

Characters and Unicode

Total characters1240936
Distinct characters87
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique182 ?
Unique (%)9.8%

Sample

1st rowSalary range for this position is: $42,405 - $45,000 per year
2nd row1. A Motor Vehicle Driver’s License valid in the State of New York is required for these positions. This license must be maintained for the duration of the assignment. 2. A Certificate of Fitness to Operate Air Compressors (A-35), issued by the New York City Fire Department is required for these positions. This certificate must be maintained for the duration of assignment. 3. A Certificate of Fitness for Low Pressure Oil Boilers (P-99), issued by the New York City Fire Department, is required for these positions and must be obtained within six months of appointment. This certificate must be maintained thereafter for the duration of employment.
3rd row1. A Motor Vehicle Driver’s License valid in the State of New York is required for these positions. This license must be maintained for the duration of the assignment. 2. A Certificate of Fitness to Operate Air Compressors (A-35), issued by the New York City Fire Department is required for these positions. This certificate must be maintained for the duration of assignment. 3. A Certificate of Fitness for Low Pressure Oil Boilers (P-99), issued by the New York City Fire Department, is required for these positions and must be obtained within six months of appointment. This certificate must be maintained thereafter for the duration of employment.
4th rowSPECIAL NOTE: 1. This is a temporary assignment for a period not to exceed three months. 2. Selected candidates will be required to travel throughout the five boroughs.
5th rowSPECIAL NOTE: 1. This is a temporary assignment for a period not to exceed three months. 2. Selected candidates will be required to travel throughout the five boroughs.

Common Values

ValueCountFrequency (%)
Appointments are subject to OMB approval. For additional information about DEP, visit www.nyc.gov/dep DEP is an equal opportunity employer with a strong commitment to the diversity of our organization and workforce. Your voluntary response to the NYCAPS on-line application section for referral information will assist us tremendously in our ability to track the success of our outreach and recruitment efforts. Please be sure to indicate your source of referral to this job. NOTE: This position is open to qualified persons with a disability who are eligible for the 55-a Program and also meet the education and experience requirements as listed in the job posting notice. Please indicate on your resume or cover letter that you would like to be considered for the position under the 55-a Program. This position is also open to non 55-a Program candidates who meet the education and experience requirements as listed in the job posting notice.87
 
3.0%
NYCHA employees applying for promotional, title or level change opportunities must have served a period of one year in their current title and level (if applicable).56
 
1.9%
**IMPORTANT NOTES TO ALL CANDIDATES: Please note: If you are called for an interview you will be required to bring to your interview copies of original documentation, such as: • A document that establishes identity for employment eligibility, such as: A Valid U.S. Passport, Permanent Resident Card/Green Card, or Driver’s license. • Proof of Education according to the education requirements of the civil service title. • Current Resume • Proof of Address/NYC Residency dated within the last 60 days, such as: Recent Utility Bill (i.e. Telephone, Cable, Mobile Phone) Additional documentation may be required to evaluate your qualification as outlined in this posting’s “Minimum Qualification Requirements” section. Examples of additional documentation may be, but not limited to: college transcript, experience verification or professional trade licenses. If after your interview you are the selected candidate you will be contacted to schedule an on-boarding appointment. By the time of this appointment you will be asked to produce the originals of the above documents along with your original Social Security card. **LOAN FORGIVENESS The federal government provides student loan forgiveness through its Public Service Loan Forgiveness Program (PSLF) to all qualifying public service employees. Working with the DOHMH qualifies you as a public service employee and you may be able to take advantage of this program while working full-time and meeting the program’s other requirements. Please visit the Public Service Loan Forgiveness Program site to view the eligibility requirements: https://studentaid.ed.gov/sa/repay-loans/forgiveness-cancellation/public-service "FINAL APPOINTMENTS ARE SUBJECT TO OFFICE OF MANAGEMENT & BUDGET APPROVAL”49
 
1.7%
**IMPORTANT NOTES TO ALL CANDIDATES: Please note: If you are called for an interview you will be required to bring to your interview copies of original documentation, such as: • A document that establishes identity for employment eligibility, such as: A Valid U.S. Passport, Permanent Resident Card/Green Card, or Driver’s license. • Proof of Education according to the education requirements of the civil service title. • Current Resume • Proof of Address/NYC Residency dated within the last 60 days, such as: Recent Utility Bill (i.e. Telephone, Cable, Mobile Phone) Additional documentation may be required to evaluate your qualification as outlined in this posting’s “Minimum Qualification Requirements” section. Examples of additional documentation may be, but not limited to: college transcript, experience verification or professional trade licenses. If after your interview you are the selected candidate you will be contacted to schedule an on-boarding appointment. By the time of this appointment you will be asked to produce the originals of the above documents along with your original Social Security card. **LOAN FORGIVENESS The federal government provides student loan forgiveness through its Public Service Loan Forgiveness Program (PSLF) to all qualifying public service employees. Working with the DOHMH qualifies you as a public service employee and you may be able to take advantage of this program while working full-time and meeting the program’s other requirements. Please visit the Public Service Loan Forgiveness Program site to view the eligibility requirements: https://studentaid.ed.gov/sa/repay-loans/forgiveness-cancellation/public-service36
 
1.2%
Note: This position is open to qualified persons with a disability who are eligible for the 55-a program. Please indicate in your resume or cover letter that you would like to be considered for the position under the 55-a program.35
 
1.2%
Appointments are subject to OMB approval. For additional information about DEP, visit www.nyc.gov/dep DEP is an equal opportunity employer with a strong commitment to the diversity of our organization and workforce. Your voluntary response to the NYCAPS on-line application section for referral information will assist us tremendously in our ability to track the success of our outreach and recruitment efforts. Please be sure to indicate your source of referral to this job. NOTE: This position is open to qualified persons with a disability who are eligible for the 55-a Program and also meet the education and experience requirements as listed in the job posting notice. Please indicate on your resume or cover letter that you would like to be considered for the position under the 55-a Program. This position is also open to non 55-a Program candidates who meet the education and experience requirements as listed in the job posting notice.27
 
0.9%
DEP is an equal opportunity employer with a strong commitment to the diversity of our organization and workforce. Your voluntary response to the NYCAPS on-line application section for referral information will assist us tremendously in our ability to track the success of our outreach and recruitment efforts. Please be sure to indicate your source of referral to this job. “NOTE: This position is open to qualified persons with a disability who are eligible for the 55-a Program and also meet the education and experience requirements as listed in the job posting notice. Please indicate on your resume or cover letter that you would like to be considered for the position under the 55-a Program. This position is also open to non 55-a Program candidates who meet the education and experience requirements as listed in the job posting notice.”22
 
0.7%
Mayor’s Office of Contract Services is an equal opportunity employer. Special accommodations provided for applicants with disabilities. Mayor’s Office of Contract Services recognizes the unique skills and strengths gained through military service. Veterans and service members of the U.S. Armed Forces are strongly encouraged to apply. STUDENT LOAN FORGIVENESS PROGRAM The U.S. Department of Education provides student loan forgiveness through the Public Service Loan Forgiveness Program (PSLFP) to qualifying public service employees. As an employee of the City of New York, you may be eligible for loan forgiveness should you meet the program’s eligibility requirements. For additional information on the PSLFP, please visit https://studentaid.ed.gov/sa/repay-loans/forgiveness-cancellation/public-service.20
 
0.7%
Appointments are subject to OMB approval. For additional information about DEP, visit www.nyc.gov/dep DEP is an equal opportunity employer with a strong commitment to the diversity of our organization and workforce. Your voluntary response to the NYCAPS on-line application section for referral information will assist us tremendously in our ability to track the success of our outreach and recruitment efforts. Please be sure to indicate your source of referral to this job.20
 
0.7%
Section 424-A of the New York Social Services Law requires an authorized agency to inquire whether a candidate for employment with child-caring responsibilities has been the subject of a child abuse and maltreatment report. The City of New York and the Administration for Children’s Services are Equal Opportunity Employers Committed to Diversity17
 
0.6%
Other values (671)1485
50.4%
(Missing)1092
37.1%

Length

2021-06-21T11:44:01.782216image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the9494
 
5.1%
to8411
 
4.5%
of5400
 
2.9%
and4683
 
2.5%
for3664
 
2.0%
be3383
 
1.8%
in3140
 
1.7%
a3128
 
1.7%
this2506
 
1.4%
your2467
 
1.3%
Other values (2124)139230
75.1%

Most occurring characters

ValueCountFrequency (%)
191764
15.5%
e113032
 
9.1%
i84436
 
6.8%
o81547
 
6.6%
t80651
 
6.5%
r66749
 
5.4%
a65800
 
5.3%
n65262
 
5.3%
s55185
 
4.4%
l41352
 
3.3%
Other values (77)395158
31.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter917772
74.0%
Space Separator191764
 
15.5%
Uppercase Letter89601
 
7.2%
Other Punctuation25478
 
2.1%
Decimal Number7255
 
0.6%
Dash Punctuation3851
 
0.3%
Close Punctuation1472
 
0.1%
Open Punctuation1425
 
0.1%
Final Punctuation1286
 
0.1%
Control468
 
< 0.1%
Other values (4)564
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e113032
12.3%
i84436
 
9.2%
o81547
 
8.9%
t80651
 
8.8%
r66749
 
7.3%
a65800
 
7.2%
n65262
 
7.1%
s55185
 
6.0%
l41352
 
4.5%
c31619
 
3.4%
Other values (17)232139
25.3%
Uppercase Letter
ValueCountFrequency (%)
P9067
 
10.1%
E8812
 
9.8%
A7303
 
8.2%
S6772
 
7.6%
N6595
 
7.4%
T6586
 
7.4%
I5384
 
6.0%
O5356
 
6.0%
C4898
 
5.5%
R4069
 
4.5%
Other values (15)24759
27.6%
Other Punctuation
ValueCountFrequency (%)
.11107
43.6%
,4707
18.5%
/2940
 
11.5%
:2607
 
10.2%
*2266
 
8.9%
665
 
2.6%
;622
 
2.4%
'296
 
1.2%
#111
 
0.4%
"81
 
0.3%
Other values (2)76
 
0.3%
Decimal Number
ValueCountFrequency (%)
53385
46.7%
2715
 
9.9%
0645
 
8.9%
1643
 
8.9%
4542
 
7.5%
6361
 
5.0%
3288
 
4.0%
8239
 
3.3%
7222
 
3.1%
9215
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
-3839
99.7%
12
 
0.3%
Final Punctuation
ValueCountFrequency (%)
886
68.9%
400
31.1%
Math Symbol
ValueCountFrequency (%)
+68
89.5%
>8
 
10.5%
Space Separator
ValueCountFrequency (%)
191764
100.0%
Currency Symbol
ValueCountFrequency (%)
$153
100.0%
Open Punctuation
ValueCountFrequency (%)
(1425
100.0%
Close Punctuation
ValueCountFrequency (%)
)1472
100.0%
Initial Punctuation
ValueCountFrequency (%)
329
100.0%
Connector Punctuation
ValueCountFrequency (%)
_6
100.0%
Control
ValueCountFrequency (%)
468
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin1007373
81.2%
Common233563
 
18.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e113032
 
11.2%
i84436
 
8.4%
o81547
 
8.1%
t80651
 
8.0%
r66749
 
6.6%
a65800
 
6.5%
n65262
 
6.5%
s55185
 
5.5%
l41352
 
4.1%
c31619
 
3.1%
Other values (42)321740
31.9%
Common
ValueCountFrequency (%)
191764
82.1%
.11107
 
4.8%
,4707
 
2.0%
-3839
 
1.6%
53385
 
1.4%
/2940
 
1.3%
:2607
 
1.1%
*2266
 
1.0%
)1472
 
0.6%
(1425
 
0.6%
Other values (25)8051
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1238634
99.8%
Punctuation2292
 
0.2%
Latin 1 Sup10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
191764
15.5%
e113032
 
9.1%
i84436
 
6.8%
o81547
 
6.6%
t80651
 
6.5%
r66749
 
5.4%
a65800
 
5.3%
n65262
 
5.3%
s55185
 
4.5%
l41352
 
3.3%
Other values (70)392856
31.7%
Punctuation
ValueCountFrequency (%)
886
38.7%
665
29.0%
400
17.5%
329
 
14.4%
12
 
0.5%
Latin 1 Sup
ValueCountFrequency (%)
§8
80.0%
è2
 
20.0%

To Apply
Categorical

HIGH CARDINALITY

Distinct893
Distinct (%)30.3%
Missing1
Missing (%)< 0.1%
Memory size23.1 KiB
Click the "Apply Now" button.
296 
Click, "APPLY NOW" Current city employees must apply via Employee Self-Service (ESS)
 
116
Click the "Apply Now" button
 
112
To apply click "Apply Now"
 
90
Click "Apply Now" button
 
54
Other values (888)
2277 

Length

Max length1730
Median length192
Mean length298.8502547
Min length12

Characters and Unicode

Total characters880114
Distinct characters93
Distinct categories14 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)7.6%

Sample

1st rowIn addition to applying through this website, also email your resume and cover letter including the following subject line: Executive Director – Business Development to: careers@sbs.nyc.gov Salary range for this position is: $85,000 - $87,000 per year NOTE: Only those candidates under consideration will be contacted.
2nd rowClick the "Apply Now" button.
3rd rowClick the "Apply Now" button.
4th rowClick the "Apply Now" button.
5th rowClick the "Apply Now" button.

Common Values

ValueCountFrequency (%)
Click the "Apply Now" button.296
 
10.0%
Click, "APPLY NOW" Current city employees must apply via Employee Self-Service (ESS)116
 
3.9%
Click the "Apply Now" button112
 
3.8%
To apply click "Apply Now"90
 
3.1%
Click "Apply Now" button54
 
1.8%
For City employees, please go to Employee Self Service (ESS), click on Recruiting Activities > Careers, and search for the Job ID # indicated above. For all other applicants, please go to www.nyc.gov/careers and search for the Job ID # indicated above. The Mayor’s Office of Management and Budget and the City of New York are Equal Opportunity Employers. You must be a City resident within 90 days of the date of appointment and you must be legally eligible to work in the United States. SUBMISSION OF A RESUME IS NOT A GUARANTEE THAT YOU WILL RECEIVE AN INTERVIEW; ONLY THOSE CANDIDATES UNDER CONSIDERATION WILL BE CONTACTED.46
 
1.6%
Click on the "Apply Now" button.43
 
1.5%
Click the “Apply Now” button41
 
1.4%
To apply, please click, "Apply Now".38
 
1.3%
Apply Online.38
 
1.3%
Other values (883)2071
70.3%

Length

2021-06-21T11:44:02.327917image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
to5302
 
3.9%
the4515
 
3.4%
for4285
 
3.2%
and4083
 
3.0%
apply2765
 
2.1%
please2462
 
1.8%
job2447
 
1.8%
be2249
 
1.7%
id2181
 
1.6%
of2116
 
1.6%
Other values (1592)101904
75.9%

Most occurring characters

ValueCountFrequency (%)
138466
 
15.7%
e71392
 
8.1%
o51499
 
5.9%
t47147
 
5.4%
i40866
 
4.6%
a40779
 
4.6%
r40082
 
4.6%
n37397
 
4.2%
s32880
 
3.7%
l32705
 
3.7%
Other values (83)346901
39.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter573635
65.2%
Space Separator138466
 
15.7%
Uppercase Letter115550
 
13.1%
Other Punctuation31152
 
3.5%
Decimal Number14677
 
1.7%
Dash Punctuation2348
 
0.3%
Close Punctuation1544
 
0.2%
Open Punctuation1437
 
0.2%
Final Punctuation529
 
0.1%
Initial Punctuation346
 
< 0.1%
Other values (4)430
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e71392
12.4%
o51499
 
9.0%
t47147
 
8.2%
i40866
 
7.1%
a40779
 
7.1%
r40082
 
7.0%
n37397
 
6.5%
s32880
 
5.7%
l32705
 
5.7%
c26347
 
4.6%
Other values (16)152541
26.6%
Uppercase Letter
ValueCountFrequency (%)
E12704
11.0%
S10705
 
9.3%
A9867
 
8.5%
I9045
 
7.8%
N8821
 
7.6%
T8142
 
7.0%
C7857
 
6.8%
O7683
 
6.6%
D6074
 
5.3%
P5385
 
4.7%
Other values (15)29267
25.3%
Other Punctuation
ValueCountFrequency (%)
.11571
37.1%
,6100
19.6%
/4862
15.6%
:3237
 
10.4%
"2345
 
7.5%
#1835
 
5.9%
*586
 
1.9%
&232
 
0.7%
;154
 
0.5%
'91
 
0.3%
Other values (6)139
 
0.4%
Decimal Number
ValueCountFrequency (%)
42155
14.7%
12097
14.3%
21847
12.6%
01750
11.9%
51685
11.5%
31282
8.7%
71274
8.7%
91061
7.2%
6773
 
5.3%
8753
 
5.1%
Math Symbol
ValueCountFrequency (%)
>176
80.4%
|32
 
14.6%
=7
 
3.2%
<4
 
1.8%
Dash Punctuation
ValueCountFrequency (%)
-2320
98.8%
28
 
1.2%
Initial Punctuation
ValueCountFrequency (%)
329
95.1%
17
 
4.9%
Final Punctuation
ValueCountFrequency (%)
338
63.9%
191
36.1%
Space Separator
ValueCountFrequency (%)
138466
100.0%
Currency Symbol
ValueCountFrequency (%)
$28
100.0%
Open Punctuation
ValueCountFrequency (%)
(1437
100.0%
Close Punctuation
ValueCountFrequency (%)
)1544
100.0%
Connector Punctuation
ValueCountFrequency (%)
_30
100.0%
Control
ValueCountFrequency (%)
153
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin689185
78.3%
Common190929
 
21.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e71392
 
10.4%
o51499
 
7.5%
t47147
 
6.8%
i40866
 
5.9%
a40779
 
5.9%
r40082
 
5.8%
n37397
 
5.4%
s32880
 
4.8%
l32705
 
4.7%
c26347
 
3.8%
Other values (41)268091
38.9%
Common
ValueCountFrequency (%)
138466
72.5%
.11571
 
6.1%
,6100
 
3.2%
/4862
 
2.5%
:3237
 
1.7%
"2345
 
1.2%
-2320
 
1.2%
42155
 
1.1%
12097
 
1.1%
21847
 
1.0%
Other values (32)15929
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII879173
99.9%
Punctuation939
 
0.1%
Latin 1 Sup2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
138466
15.7%
e71392
 
8.1%
o51499
 
5.9%
t47147
 
5.4%
i40866
 
4.6%
a40779
 
4.6%
r40082
 
4.6%
n37397
 
4.3%
s32880
 
3.7%
l32705
 
3.7%
Other values (76)345960
39.4%
Punctuation
ValueCountFrequency (%)
338
36.0%
329
35.0%
191
20.3%
36
 
3.8%
28
 
3.0%
17
 
1.8%
Latin 1 Sup
ValueCountFrequency (%)
¿2
100.0%

Hours/Shift
Categorical

HIGH CARDINALITY
MISSING

Distinct181
Distinct (%)20.5%
Missing2062
Missing (%)70.0%
Memory size23.1 KiB
35 Hours
134 
35 hours per week
 
47
Day - Due to the necessary technical support duties of this position in a 24/7 operation, candidate may be required to work various shifts such as weekends and/or nights/evenings.
 
38
35 hours per week / day
 
36
35hrs
 
33
Other values (176)
596 

Length

Max length247
Median length23
Mean length46.76244344
Min length3

Characters and Unicode

Total characters41338
Distinct characters71
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)3.5%

Sample

1st row35 Hours per week/Day shift
2nd rowMonday through Friday 9;00 am - 5:00 pm
3rd rowDay
4th rowHours: 17 hours per week when school is in session, or 35 hours per week during the summer vacation. Shift: Weekdays/minimum three (3) mornings per week.
5th rowHours: 17 hours per week when school is in session, or 35 hours per week during the summer vacation. Shift: Weekdays/minimum three (3) mornings per week.

Common Values

ValueCountFrequency (%)
35 Hours134
 
4.5%
35 hours per week47
 
1.6%
Day - Due to the necessary technical support duties of this position in a 24/7 operation, candidate may be required to work various shifts such as weekends and/or nights/evenings.38
 
1.3%
35 hours per week / day36
 
1.2%
35hrs33
 
1.1%
Unless otherwise indicated, all positions require a five-day workweek.24
 
0.8%
DAY, 9-5; ON OCCASION, CANDIDATES WILL BE REQUIRED TO WORK EVENINGS AND/OR ON WEEKENDS TO SUPPORT THE DUTIES OF THE POSITION.22
 
0.7%
Monday – Friday, 9am to 5pm.19
 
0.6%
35 hours18
 
0.6%
35 hours per week.17
 
0.6%
Other values (171)496
 
16.8%
(Missing)2062
70.0%

Length

2021-06-21T11:44:02.859383image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
hours513
 
7.0%
35488
 
6.6%
to374
 
5.1%
week287
 
3.9%
per278
 
3.8%
241
 
3.3%
be231
 
3.1%
day187
 
2.5%
the180
 
2.4%
work158
 
2.1%
Other values (241)4420
60.1%

Most occurring characters

ValueCountFrequency (%)
6591
15.9%
e3455
 
8.4%
s2438
 
5.9%
o2243
 
5.4%
r2120
 
5.1%
i2032
 
4.9%
a1919
 
4.6%
n1750
 
4.2%
t1647
 
4.0%
u1308
 
3.2%
Other values (61)15835
38.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter26836
64.9%
Space Separator6591
 
15.9%
Uppercase Letter4396
 
10.6%
Decimal Number1869
 
4.5%
Other Punctuation1292
 
3.1%
Dash Punctuation298
 
0.7%
Open Punctuation25
 
0.1%
Close Punctuation25
 
0.1%
Final Punctuation4
 
< 0.1%
Math Symbol2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e3455
12.9%
s2438
 
9.1%
o2243
 
8.4%
r2120
 
7.9%
i2032
 
7.6%
a1919
 
7.2%
n1750
 
6.5%
t1647
 
6.1%
u1308
 
4.9%
d1260
 
4.7%
Other values (15)6664
24.8%
Uppercase Letter
ValueCountFrequency (%)
D492
11.2%
E383
 
8.7%
H373
 
8.5%
O370
 
8.4%
T351
 
8.0%
S338
 
7.7%
N283
 
6.4%
I251
 
5.7%
P179
 
4.1%
A175
 
4.0%
Other values (13)1201
27.3%
Decimal Number
ValueCountFrequency (%)
5621
33.2%
3544
29.1%
0204
 
10.9%
4150
 
8.0%
7108
 
5.8%
2105
 
5.6%
9102
 
5.5%
123
 
1.2%
810
 
0.5%
62
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/543
42.0%
.323
25.0%
,270
20.9%
:91
 
7.0%
;47
 
3.6%
*18
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
-249
83.6%
49
 
16.4%
Space Separator
ValueCountFrequency (%)
6591
100.0%
Open Punctuation
ValueCountFrequency (%)
(25
100.0%
Close Punctuation
ValueCountFrequency (%)
)25
100.0%
Math Symbol
ValueCountFrequency (%)
+2
100.0%
Final Punctuation
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin31232
75.6%
Common10106
 
24.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e3455
 
11.1%
s2438
 
7.8%
o2243
 
7.2%
r2120
 
6.8%
i2032
 
6.5%
a1919
 
6.1%
n1750
 
5.6%
t1647
 
5.3%
u1308
 
4.2%
d1260
 
4.0%
Other values (38)11060
35.4%
Common
ValueCountFrequency (%)
6591
65.2%
5621
 
6.1%
3544
 
5.4%
/543
 
5.4%
.323
 
3.2%
,270
 
2.7%
-249
 
2.5%
0204
 
2.0%
4150
 
1.5%
7108
 
1.1%
Other values (13)503
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII41285
99.9%
Punctuation53
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6591
16.0%
e3455
 
8.4%
s2438
 
5.9%
o2243
 
5.4%
r2120
 
5.1%
i2032
 
4.9%
a1919
 
4.6%
n1750
 
4.2%
t1647
 
4.0%
u1308
 
3.2%
Other values (59)15782
38.2%
Punctuation
ValueCountFrequency (%)
49
92.5%
4
 
7.5%

Residency Requirement
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct50
Distinct (%)1.7%
Missing4
Missing (%)0.1%
Memory size23.1 KiB
New York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.
1705 
New York City Residency is not required for this position
637 
NYCHA has no residency requirements.
222 
New York City Residency is not required for this position.
216 
This position is exempt from NYC residency requirements.
 
19
Other values (45)
 
143

Length

Max length793
Median length400
Mean length259.8140721
Min length33

Characters and Unicode

Total characters764373
Distinct characters67
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st rowNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.
2nd rowNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.
3rd rowNYCHA has no residency requirements.
4th rowNYCHA has no residency requirements.
5th rowNYCHA has no residency requirement.

Common Values

ValueCountFrequency (%)
New York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.1705
57.9%
New York City Residency is not required for this position637
 
21.6%
NYCHA has no residency requirements.222
 
7.5%
New York City Residency is not required for this position.216
 
7.3%
This position is exempt from NYC residency requirements.19
 
0.6%
New York City residency is not required for this position.16
 
0.5%
Residency in New York City, Nassau, Orange, Rockland, Suffolk, Putnam or Westchester counties required for employees with over two years of city service. New York City residency required within 90 days of hire for all other candidates.15
 
0.5%
Residency in New York City, Nassau, Orange, Rockland, Suffolk, Putnam or Westchester counties required for employees with over two years of city service. New York City residency required within 90 days of hiring for all other candidates.10
 
0.3%
City Residency is not required for this position8
 
0.3%
New York City Residency is not required for this position; however, you must reside in New York State.7
 
0.2%
Other values (40)87
 
3.0%

Length

2021-06-21T11:44:03.279967image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the6933
 
5.7%
city6172
 
5.1%
to5199
 
4.3%
residency4681
 
3.9%
for4433
 
3.7%
of3562
 
2.9%
in3505
 
2.9%
york2725
 
2.2%
new2723
 
2.2%
required2712
 
2.2%
Other values (184)78469
64.8%

Most occurring characters

ValueCountFrequency (%)
118277
15.5%
e91422
12.0%
i56053
 
7.3%
t52952
 
6.9%
r43187
 
5.6%
o41866
 
5.5%
s39555
 
5.2%
n38515
 
5.0%
a31765
 
4.2%
y24795
 
3.2%
Other values (57)225986
29.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter590367
77.2%
Space Separator118277
 
15.5%
Uppercase Letter32341
 
4.2%
Other Punctuation18092
 
2.4%
Decimal Number5284
 
0.7%
Dash Punctuation8
 
< 0.1%
Open Punctuation2
 
< 0.1%
Close Punctuation2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e91422
15.5%
i56053
 
9.5%
t52952
 
9.0%
r43187
 
7.3%
o41866
 
7.1%
s39555
 
6.7%
n38515
 
6.5%
a31765
 
5.4%
y24795
 
4.2%
l19177
 
3.2%
Other values (16)151080
25.6%
Uppercase Letter
ValueCountFrequency (%)
C8180
25.3%
N4814
14.9%
Y3029
 
9.4%
R2738
 
8.5%
H1991
 
6.2%
E1843
 
5.7%
S1836
 
5.7%
T1834
 
5.7%
O1826
 
5.6%
P1813
 
5.6%
Other values (14)2437
 
7.5%
Decimal Number
ValueCountFrequency (%)
01777
33.6%
91773
33.6%
21722
32.6%
84
 
0.1%
14
 
0.1%
32
 
< 0.1%
72
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
,12209
67.5%
.5790
32.0%
*68
 
0.4%
;11
 
0.1%
:8
 
< 0.1%
/6
 
< 0.1%
Space Separator
ValueCountFrequency (%)
118277
100.0%
Dash Punctuation
ValueCountFrequency (%)
-8
100.0%
Open Punctuation
ValueCountFrequency (%)
(2
100.0%
Close Punctuation
ValueCountFrequency (%)
)2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin622708
81.5%
Common141665
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e91422
14.7%
i56053
 
9.0%
t52952
 
8.5%
r43187
 
6.9%
o41866
 
6.7%
s39555
 
6.4%
n38515
 
6.2%
a31765
 
5.1%
y24795
 
4.0%
l19177
 
3.1%
Other values (40)183421
29.5%
Common
ValueCountFrequency (%)
118277
83.5%
,12209
 
8.6%
.5790
 
4.1%
01777
 
1.3%
91773
 
1.3%
21722
 
1.2%
*68
 
< 0.1%
;11
 
< 0.1%
-8
 
< 0.1%
:8
 
< 0.1%
Other values (7)22
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII764373
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
118277
15.5%
e91422
12.0%
i56053
 
7.3%
t52952
 
6.9%
r43187
 
5.6%
o41866
 
5.5%
s39555
 
5.2%
n38515
 
5.0%
a31765
 
4.2%
y24795
 
3.2%
Other values (57)225986
29.6%

Posting Date
Categorical

HIGH CARDINALITY

Distinct493
Distinct (%)16.8%
Missing4
Missing (%)0.1%
Memory size23.1 KiB
2019-11-01T00:00:00.000
 
64
2019-09-30T00:00:00.000
 
60
2019-11-26T00:00:00.000
 
58
2019-11-27T00:00:00.000
 
55
2019-12-10T00:00:00.000
 
53
Other values (488)
2652 

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters67666
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)3.1%

Sample

1st row2011-06-24T00:00:00.000
2nd row2012-01-26T00:00:00.000
3rd row2013-10-24T00:00:00.000
4th row2013-10-24T00:00:00.000
5th row2014-01-09T00:00:00.000

Common Values

ValueCountFrequency (%)
2019-11-01T00:00:00.00064
 
2.2%
2019-09-30T00:00:00.00060
 
2.0%
2019-11-26T00:00:00.00058
 
2.0%
2019-11-27T00:00:00.00055
 
1.9%
2019-12-10T00:00:00.00053
 
1.8%
2019-12-06T00:00:00.00052
 
1.8%
2019-12-13T00:00:00.00052
 
1.8%
2019-12-11T00:00:00.00048
 
1.6%
2019-10-28T00:00:00.00045
 
1.5%
2019-11-22T00:00:00.00040
 
1.4%
Other values (483)2415
82.0%

Length

2021-06-21T11:44:03.675553image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-11-01t00:00:00.00064
 
2.2%
2019-09-30t00:00:00.00060
 
2.0%
2019-11-26t00:00:00.00058
 
2.0%
2019-11-27t00:00:00.00055
 
1.9%
2019-12-10t00:00:00.00053
 
1.8%
2019-12-06t00:00:00.00052
 
1.8%
2019-12-13t00:00:00.00052
 
1.8%
2019-12-11t00:00:00.00048
 
1.6%
2019-10-28t00:00:00.00045
 
1.5%
2019-11-22t00:00:00.00040
 
1.4%
Other values (483)2415
82.1%

Most occurring characters

ValueCountFrequency (%)
032515
48.1%
16352
 
9.4%
-5884
 
8.7%
:5884
 
8.7%
24747
 
7.0%
T2942
 
4.3%
.2942
 
4.3%
92769
 
4.1%
8913
 
1.3%
6642
 
0.9%
Other values (4)2076
 
3.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number50014
73.9%
Other Punctuation8826
 
13.0%
Dash Punctuation5884
 
8.7%
Uppercase Letter2942
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032515
65.0%
16352
 
12.7%
24747
 
9.5%
92769
 
5.5%
8913
 
1.8%
6642
 
1.3%
7610
 
1.2%
3607
 
1.2%
5448
 
0.9%
4411
 
0.8%
Other Punctuation
ValueCountFrequency (%)
:5884
66.7%
.2942
33.3%
Dash Punctuation
ValueCountFrequency (%)
-5884
100.0%
Uppercase Letter
ValueCountFrequency (%)
T2942
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common64724
95.7%
Latin2942
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
032515
50.2%
16352
 
9.8%
-5884
 
9.1%
:5884
 
9.1%
24747
 
7.3%
.2942
 
4.5%
92769
 
4.3%
8913
 
1.4%
6642
 
1.0%
7610
 
0.9%
Other values (3)1466
 
2.3%
Latin
ValueCountFrequency (%)
T2942
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII67666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032515
48.1%
16352
 
9.4%
-5884
 
8.7%
:5884
 
8.7%
24747
 
7.0%
T2942
 
4.3%
.2942
 
4.3%
92769
 
4.1%
8913
 
1.3%
6642
 
0.9%
Other values (4)2076
 
3.1%

Posting Updated
Categorical

HIGH CARDINALITY

Distinct487
Distinct (%)16.6%
Missing4
Missing (%)0.1%
Memory size23.1 KiB
2019-12-13T00:00:00.000
 
82
2019-12-16T00:00:00.000
 
72
2019-12-11T00:00:00.000
 
68
2019-11-27T00:00:00.000
 
67
2019-12-10T00:00:00.000
 
66
Other values (482)
2587 

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters67666
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)2.8%

Sample

1st row2011-06-24T00:00:00.000
2nd row2012-01-26T00:00:00.000
3rd row2013-12-12T00:00:00.000
4th row2013-12-12T00:00:00.000
5th row2014-01-08T00:00:00.000

Common Values

ValueCountFrequency (%)
2019-12-13T00:00:00.00082
 
2.8%
2019-12-16T00:00:00.00072
 
2.4%
2019-12-11T00:00:00.00068
 
2.3%
2019-11-27T00:00:00.00067
 
2.3%
2019-12-10T00:00:00.00066
 
2.2%
2019-11-26T00:00:00.00066
 
2.2%
2019-12-12T00:00:00.00062
 
2.1%
2019-12-05T00:00:00.00056
 
1.9%
2019-12-06T00:00:00.00047
 
1.6%
2019-11-04T00:00:00.00045
 
1.5%
Other values (477)2311
78.4%

Length

2021-06-21T11:44:04.085460image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2019-12-13t00:00:00.00082
 
2.8%
2019-12-16t00:00:00.00072
 
2.4%
2019-12-11t00:00:00.00068
 
2.3%
2019-11-27t00:00:00.00067
 
2.3%
2019-12-10t00:00:00.00066
 
2.2%
2019-11-26t00:00:00.00066
 
2.2%
2019-12-12t00:00:00.00062
 
2.1%
2019-12-05t00:00:00.00056
 
1.9%
2019-12-06t00:00:00.00047
 
1.6%
2019-11-04t00:00:00.00045
 
1.5%
Other values (477)2311
78.6%

Most occurring characters

ValueCountFrequency (%)
032279
47.7%
16680
 
9.9%
-5884
 
8.7%
:5884
 
8.7%
24878
 
7.2%
T2942
 
4.3%
.2942
 
4.3%
92782
 
4.1%
8817
 
1.2%
6632
 
0.9%
Other values (4)1946
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number50014
73.9%
Other Punctuation8826
 
13.0%
Dash Punctuation5884
 
8.7%
Uppercase Letter2942
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
032279
64.5%
16680
 
13.4%
24878
 
9.8%
92782
 
5.6%
8817
 
1.6%
6632
 
1.3%
7559
 
1.1%
3520
 
1.0%
5476
 
1.0%
4391
 
0.8%
Other Punctuation
ValueCountFrequency (%)
:5884
66.7%
.2942
33.3%
Dash Punctuation
ValueCountFrequency (%)
-5884
100.0%
Uppercase Letter
ValueCountFrequency (%)
T2942
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common64724
95.7%
Latin2942
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
032279
49.9%
16680
 
10.3%
-5884
 
9.1%
:5884
 
9.1%
24878
 
7.5%
.2942
 
4.5%
92782
 
4.3%
8817
 
1.3%
6632
 
1.0%
7559
 
0.9%
Other values (3)1387
 
2.1%
Latin
ValueCountFrequency (%)
T2942
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII67666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
032279
47.7%
16680
 
9.9%
-5884
 
8.7%
:5884
 
8.7%
24878
 
7.2%
T2942
 
4.3%
.2942
 
4.3%
92782
 
4.1%
8817
 
1.2%
6632
 
0.9%
Other values (4)1946
 
2.9%

Process Date
Categorical

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing4
Missing (%)0.1%
Memory size23.1 KiB
2019-12-17T00:00:00.000
2942 

Length

Max length23
Median length23
Mean length23
Min length23

Characters and Unicode

Total characters67666
Distinct characters9
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019-12-17T00:00:00.000
2nd row2019-12-17T00:00:00.000
3rd row2019-12-17T00:00:00.000
4th row2019-12-17T00:00:00.000
5th row2019-12-17T00:00:00.000

Common Values

ValueCountFrequency (%)
2019-12-17T00:00:00.0002942
99.9%
(Missing)4
 
0.1%

Length

2021-06-21T11:44:04.338968image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:04.433690image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
2019-12-17t00:00:00.0002942
100.0%

Most occurring characters

ValueCountFrequency (%)
029420
43.5%
18826
 
13.0%
25884
 
8.7%
-5884
 
8.7%
:5884
 
8.7%
92942
 
4.3%
72942
 
4.3%
T2942
 
4.3%
.2942
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number50014
73.9%
Other Punctuation8826
 
13.0%
Dash Punctuation5884
 
8.7%
Uppercase Letter2942
 
4.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
029420
58.8%
18826
 
17.6%
25884
 
11.8%
92942
 
5.9%
72942
 
5.9%
Other Punctuation
ValueCountFrequency (%)
:5884
66.7%
.2942
33.3%
Dash Punctuation
ValueCountFrequency (%)
-5884
100.0%
Uppercase Letter
ValueCountFrequency (%)
T2942
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common64724
95.7%
Latin2942
 
4.3%

Most frequent character per script

Common
ValueCountFrequency (%)
029420
45.5%
18826
 
13.6%
25884
 
9.1%
-5884
 
9.1%
:5884
 
9.1%
92942
 
4.5%
72942
 
4.5%
.2942
 
4.5%
Latin
ValueCountFrequency (%)
T2942
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII67666
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
029420
43.5%
18826
 
13.0%
25884
 
8.7%
-5884
 
8.7%
:5884
 
8.7%
92942
 
4.3%
72942
 
4.3%
T2942
 
4.3%
.2942
 
4.3%

FormalEducation
Categorical

HIGH CORRELATION
MISSING

Distinct9
Distinct (%)0.3%
Missing52
Missing (%)1.8%
Memory size23.1 KiB
Bachelor�s degree (BA, BS, B.Eng., etc.)
1442 
Master�s degree (MA, MS, M.Eng., MBA, etc.)
716 
Some college/university study without earning a degree
319 
Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)
179 
Associate degree
 
92
Other values (4)
146 

Length

Max length82
Median length40
Mean length43.96129924
Min length16

Characters and Unicode

Total characters127224
Distinct characters39
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBachelor�s degree (BA, BS, B.Eng., etc.)
2nd rowBachelor�s degree (BA, BS, B.Eng., etc.)
3rd rowAssociate degree
4th rowBachelor�s degree (BA, BS, B.Eng., etc.)
5th rowSome college/university study without earning a degree

Common Values

ValueCountFrequency (%)
Bachelor�s degree (BA, BS, B.Eng., etc.)1442
48.9%
Master�s degree (MA, MS, M.Eng., MBA, etc.)716
24.3%
Some college/university study without earning a degree319
 
10.8%
Secondary school (e.g. American high school, German Realschule or Gymnasium, etc.)179
 
6.1%
Associate degree92
 
3.1%
Other doctoral degree (Ph.D, Ed.D., etc.)75
 
2.5%
Professional degree (JD, MD, etc.)43
 
1.5%
Primary/elementary school17
 
0.6%
I never completed any formal education11
 
0.4%
(Missing)52
 
1.8%

Length

2021-06-21T11:44:04.673367image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:04.781604image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
degree2687
14.3%
etc2455
13.0%
ba1442
 
7.7%
b.eng1442
 
7.7%
bachelor�s1442
 
7.7%
bs1442
 
7.7%
ma716
 
3.8%
mba716
 
3.8%
ms716
 
3.8%
m.eng716
 
3.8%
Other values (31)5041
26.8%

Most occurring characters

ValueCountFrequency (%)
15921
 
12.5%
e15659
 
12.3%
,7784
 
6.1%
.7354
 
5.8%
B6484
 
5.1%
r6465
 
5.1%
g5841
 
4.6%
c5317
 
4.2%
t4728
 
3.7%
s4515
 
3.5%
Other values (29)47156
37.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter69583
54.7%
Uppercase Letter19178
 
15.1%
Space Separator15921
 
12.5%
Other Punctuation15474
 
12.2%
Open Punctuation2455
 
1.9%
Close Punctuation2455
 
1.9%
Other Symbol2158
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e15659
22.5%
r6465
9.3%
g5841
 
8.4%
c5317
 
7.6%
t4728
 
6.8%
s4515
 
6.5%
a3968
 
5.7%
n3924
 
5.6%
o3868
 
5.6%
d3357
 
4.8%
Other values (10)11941
17.2%
Uppercase Letter
ValueCountFrequency (%)
B6484
33.8%
M3623
18.9%
A3145
16.4%
S2656
13.8%
E2233
 
11.6%
G358
 
1.9%
D236
 
1.2%
R179
 
0.9%
P135
 
0.7%
O75
 
0.4%
Other values (2)54
 
0.3%
Other Punctuation
ValueCountFrequency (%)
,7784
50.3%
.7354
47.5%
/336
 
2.2%
Other Symbol
ValueCountFrequency (%)
2158
100.0%
Space Separator
ValueCountFrequency (%)
15921
100.0%
Open Punctuation
ValueCountFrequency (%)
(2455
100.0%
Close Punctuation
ValueCountFrequency (%)
)2455
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin88761
69.8%
Common38463
30.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e15659
17.6%
B6484
 
7.3%
r6465
 
7.3%
g5841
 
6.6%
c5317
 
6.0%
t4728
 
5.3%
s4515
 
5.1%
a3968
 
4.5%
n3924
 
4.4%
o3868
 
4.4%
Other values (22)27992
31.5%
Common
ValueCountFrequency (%)
15921
41.4%
,7784
20.2%
.7354
19.1%
(2455
 
6.4%
)2455
 
6.4%
2158
 
5.6%
/336
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII125066
98.3%
Specials2158
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15921
 
12.7%
e15659
 
12.5%
,7784
 
6.2%
.7354
 
5.9%
B6484
 
5.2%
r6465
 
5.2%
g5841
 
4.7%
c5317
 
4.3%
t4728
 
3.8%
s4515
 
3.6%
Other values (28)44998
36.0%
Specials
ValueCountFrequency (%)
2158
100.0%

UndergradMajor
Categorical

HIGH CORRELATION
MISSING

Distinct12
Distinct (%)0.5%
Missing322
Missing (%)10.9%
Memory size23.1 KiB
Computer science, computer engineering, or software engineering
1698 
Information systems, information technology, or system administration
247 
Another engineering discipline (ex. civil, electrical, mechanical)
205 
A natural science (ex. biology, chemistry, physics)
 
109
Mathematics or statistics
 
86
Other values (7)
279 

Length

Max length69
Median length63
Mean length60.82583841
Min length24

Characters and Unicode

Total characters159607
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMathematics or statistics
2nd rowA natural science (ex. biology, chemistry, physics)
3rd rowComputer science, computer engineering, or software engineering
4th rowComputer science, computer engineering, or software engineering
5th rowComputer science, computer engineering, or software engineering

Common Values

ValueCountFrequency (%)
Computer science, computer engineering, or software engineering1698
57.6%
Information systems, information technology, or system administration247
 
8.4%
Another engineering discipline (ex. civil, electrical, mechanical)205
 
7.0%
A natural science (ex. biology, chemistry, physics)109
 
3.7%
Mathematics or statistics86
 
2.9%
A business discipline (ex. accounting, finance, marketing)65
 
2.2%
Web development or web design64
 
2.2%
A humanities discipline (ex. literature, history, philosophy)48
 
1.6%
Fine arts or performing arts (ex. graphic design, music, studio art)38
 
1.3%
A social science (ex. anthropology, psychology, political science)38
 
1.3%
Other values (2)26
 
0.9%
(Missing)322
 
10.9%

Length

2021-06-21T11:44:05.177829image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
engineering3601
20.0%
computer3396
18.8%
or2133
11.8%
science1886
10.5%
software1698
9.4%
ex506
 
2.8%
information494
 
2.7%
discipline318
 
1.8%
a286
 
1.6%
systems247
 
1.4%
Other values (43)3475
19.3%

Most occurring characters

ValueCountFrequency (%)
e23181
14.5%
n16002
10.0%
15416
9.7%
i13841
 
8.7%
r12750
 
8.0%
o10023
 
6.3%
t8498
 
5.3%
g7948
 
5.0%
c7861
 
4.9%
s6727
 
4.2%
Other values (25)37360
23.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter135147
84.7%
Space Separator15416
 
9.7%
Other Punctuation5408
 
3.4%
Uppercase Letter2624
 
1.6%
Open Punctuation506
 
0.3%
Close Punctuation506
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e23181
17.2%
n16002
11.8%
i13841
10.2%
r12750
9.4%
o10023
7.4%
t8498
 
6.3%
g7948
 
5.9%
c7861
 
5.8%
s6727
 
5.0%
m5310
 
3.9%
Other values (14)23006
17.0%
Uppercase Letter
ValueCountFrequency (%)
C1698
64.7%
A468
 
17.8%
I270
 
10.3%
M86
 
3.3%
W64
 
2.4%
F38
 
1.4%
Other Punctuation
ValueCountFrequency (%)
,4902
90.6%
.506
 
9.4%
Space Separator
ValueCountFrequency (%)
15416
100.0%
Open Punctuation
ValueCountFrequency (%)
(506
100.0%
Close Punctuation
ValueCountFrequency (%)
)506
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin137771
86.3%
Common21836
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e23181
16.8%
n16002
11.6%
i13841
10.0%
r12750
9.3%
o10023
 
7.3%
t8498
 
6.2%
g7948
 
5.8%
c7861
 
5.7%
s6727
 
4.9%
m5310
 
3.9%
Other values (20)25630
18.6%
Common
ValueCountFrequency (%)
15416
70.6%
,4902
 
22.4%
(506
 
2.3%
.506
 
2.3%
)506
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII159607
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e23181
14.5%
n16002
10.0%
15416
9.7%
i13841
 
8.7%
r12750
 
8.0%
o10023
 
6.3%
t8498
 
5.3%
g7948
 
5.0%
c7861
 
4.9%
s6727
 
4.2%
Other values (25)37360
23.4%

CompanySize
Categorical

HIGH CORRELATION

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
20 to 99 employees
719 
100 to 499 employees
580 
10,000 or more employees
387 
10 to 19 employees
329 
1,000 to 4,999 employees
316 
Other values (3)
615 

Length

Max length24
Median length20
Mean length20.69653768
Min length18

Characters and Unicode

Total characters60972
Distinct characters22
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20 to 99 employees
2nd row10,000 or more employees
3rd row20 to 99 employees
4th row100 to 499 employees
5th row10,000 or more employees

Common Values

ValueCountFrequency (%)
20 to 99 employees719
24.4%
100 to 499 employees580
19.7%
10,000 or more employees387
13.1%
10 to 19 employees329
11.2%
1,000 to 4,999 employees316
10.7%
Fewer than 10 employees304
10.3%
500 to 999 employees205
 
7.0%
5,000 to 9,999 employees106
 
3.6%

Length

2021-06-21T11:44:05.462885image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:05.563416image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
employees2946
25.0%
to2255
19.1%
20719
 
6.1%
99719
 
6.1%
10633
 
5.4%
100580
 
4.9%
499580
 
4.9%
or387
 
3.3%
more387
 
3.3%
10,000387
 
3.3%
Other values (9)2191
18.6%

Most occurring characters

ValueCountFrequency (%)
e9833
16.1%
8838
14.5%
o5975
9.8%
05736
9.4%
94914
8.1%
m3333
 
5.5%
p2946
 
4.8%
l2946
 
4.8%
y2946
 
4.8%
s2946
 
4.8%
Other values (12)10559
17.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter35778
58.7%
Decimal Number14821
24.3%
Space Separator8838
 
14.5%
Other Punctuation1231
 
2.0%
Uppercase Letter304
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e9833
27.5%
o5975
16.7%
m3333
 
9.3%
p2946
 
8.2%
l2946
 
8.2%
y2946
 
8.2%
s2946
 
8.2%
t2559
 
7.2%
r1078
 
3.0%
w304
 
0.8%
Other values (3)912
 
2.5%
Decimal Number
ValueCountFrequency (%)
05736
38.7%
94914
33.2%
12245
 
15.1%
4896
 
6.0%
2719
 
4.9%
5311
 
2.1%
Space Separator
ValueCountFrequency (%)
8838
100.0%
Other Punctuation
ValueCountFrequency (%)
,1231
100.0%
Uppercase Letter
ValueCountFrequency (%)
F304
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin36082
59.2%
Common24890
40.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e9833
27.3%
o5975
16.6%
m3333
 
9.2%
p2946
 
8.2%
l2946
 
8.2%
y2946
 
8.2%
s2946
 
8.2%
t2559
 
7.1%
r1078
 
3.0%
F304
 
0.8%
Other values (4)1216
 
3.4%
Common
ValueCountFrequency (%)
8838
35.5%
05736
23.0%
94914
19.7%
12245
 
9.0%
,1231
 
4.9%
4896
 
3.6%
2719
 
2.9%
5311
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII60972
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e9833
16.1%
8838
14.5%
o5975
9.8%
05736
9.4%
94914
8.1%
m3333
 
5.5%
p2946
 
4.8%
l2946
 
4.8%
y2946
 
4.8%
s2946
 
4.8%
Other values (12)10559
17.3%

DevType
Categorical

HIGH CARDINALITY
MISSING

Distinct810
Distinct (%)27.9%
Missing45
Missing (%)1.5%
Memory size23.1 KiB
Full-stack developer
225 
Back-end developer
219 
Back-end developer;Front-end developer;Full-stack developer
 
180
Mobile developer
 
141
Back-end developer;Full-stack developer
 
120
Other values (805)
2016 

Length

Max length497
Median length53
Mean length61.74077904
Min length7

Characters and Unicode

Total characters179110
Distinct characters42
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique579 ?
Unique (%)20.0%

Sample

1st rowFull-stack developer
2nd rowDatabase administrator;DevOps specialist;Full-stack developer;System administrator
3rd rowEngineering manager;Full-stack developer
4th rowFull-stack developer
5th rowData or business analyst;Desktop or enterprise applications developer;Game or graphics developer;QA or test developer;Student

Common Values

ValueCountFrequency (%)
Full-stack developer225
 
7.6%
Back-end developer219
 
7.4%
Back-end developer;Front-end developer;Full-stack developer180
 
6.1%
Mobile developer141
 
4.8%
Back-end developer;Full-stack developer120
 
4.1%
Front-end developer110
 
3.7%
Back-end developer;Front-end developer38
 
1.3%
Front-end developer;Full-stack developer37
 
1.3%
Back-end developer;Front-end developer;Full-stack developer;Mobile developer36
 
1.2%
Back-end developer;Desktop or enterprise applications developer;Front-end developer;Full-stack developer35
 
1.2%
Other values (800)1760
59.7%
(Missing)45
 
1.5%

Length

2021-06-21T11:44:05.977998image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
developer2045
 
13.8%
back-end1701
 
11.5%
or1459
 
9.9%
developer;full-stack992
 
6.7%
applications628
 
4.3%
developer;front-end533
 
3.6%
enterprise476
 
3.2%
developer;mobile339
 
2.3%
administrator329
 
2.2%
full-stack264
 
1.8%
Other values (165)6001
40.6%

Most occurring characters

ValueCountFrequency (%)
e27936
15.6%
r12279
 
6.9%
11866
 
6.6%
o10870
 
6.1%
l10803
 
6.0%
a10656
 
5.9%
d10350
 
5.8%
t9226
 
5.2%
p8868
 
5.0%
n8449
 
4.7%
Other values (32)57807
32.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter148085
82.7%
Space Separator11866
 
6.6%
Uppercase Letter9139
 
5.1%
Other Punctuation5523
 
3.1%
Dash Punctuation4345
 
2.4%
Open Punctuation76
 
< 0.1%
Close Punctuation76
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e27936
18.9%
r12279
8.3%
o10870
 
7.3%
l10803
 
7.3%
a10656
 
7.2%
d10350
 
7.0%
t9226
 
6.2%
p8868
 
6.0%
n8449
 
5.7%
s8235
 
5.6%
Other values (12)30413
20.5%
Uppercase Letter
ValueCountFrequency (%)
F2568
28.1%
D1974
21.6%
B1701
18.6%
M551
 
6.0%
S529
 
5.8%
E485
 
5.3%
O466
 
5.1%
C228
 
2.5%
Q173
 
1.9%
A173
 
1.9%
Other values (3)291
 
3.2%
Other Punctuation
ValueCountFrequency (%)
;5295
95.9%
,152
 
2.8%
.76
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
-4345
100.0%
Space Separator
ValueCountFrequency (%)
11866
100.0%
Open Punctuation
ValueCountFrequency (%)
(76
100.0%
Close Punctuation
ValueCountFrequency (%)
)76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin157224
87.8%
Common21886
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e27936
17.8%
r12279
 
7.8%
o10870
 
6.9%
l10803
 
6.9%
a10656
 
6.8%
d10350
 
6.6%
t9226
 
5.9%
p8868
 
5.6%
n8449
 
5.4%
s8235
 
5.2%
Other values (25)39552
25.2%
Common
ValueCountFrequency (%)
11866
54.2%
;5295
24.2%
-4345
 
19.9%
,152
 
0.7%
(76
 
0.3%
.76
 
0.3%
)76
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII179110
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e27936
15.6%
r12279
 
6.9%
11866
 
6.6%
o10870
 
6.1%
l10803
 
6.0%
a10656
 
5.9%
d10350
 
5.8%
t9226
 
5.2%
p8868
 
5.0%
n8449
 
4.7%
Other values (32)57807
32.3%

YearsCoding
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct11
Distinct (%)0.4%
Missing3
Missing (%)0.1%
Memory size23.1 KiB
3-5 years
699 
6-8 years
630 
9-11 years
443 
12-14 years
277 
0-2 years
248 
Other values (6)
646 

Length

Max length16
Median length9
Mean length9.935779817
Min length9

Characters and Unicode

Total characters29241
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3-5 years
2nd row30 or more years
3rd row24-26 years
4th row18-20 years
5th row6-8 years

Common Values

ValueCountFrequency (%)
3-5 years699
23.7%
6-8 years630
21.4%
9-11 years443
15.0%
12-14 years277
 
9.4%
0-2 years248
 
8.4%
15-17 years205
 
7.0%
18-20 years179
 
6.1%
30 or more years93
 
3.2%
21-23 years82
 
2.8%
24-26 years54
 
1.8%

Length

2021-06-21T11:44:06.690120image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
years2943
48.5%
3-5699
 
11.5%
6-8630
 
10.4%
9-11443
 
7.3%
12-14277
 
4.6%
0-2248
 
4.1%
15-17205
 
3.4%
18-20179
 
2.9%
more93
 
1.5%
or93
 
1.5%
Other values (4)262
 
4.3%

Most occurring characters

ValueCountFrequency (%)
3129
10.7%
r3129
10.7%
e3036
10.4%
y2943
10.1%
a2943
10.1%
s2943
10.1%
-2850
9.7%
12111
7.2%
21042
 
3.6%
5904
 
3.1%
Other values (9)4211
14.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter15273
52.2%
Decimal Number7989
27.3%
Space Separator3129
 
10.7%
Dash Punctuation2850
 
9.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
12111
26.4%
21042
13.0%
5904
11.3%
3874
10.9%
8809
 
10.1%
6684
 
8.6%
0520
 
6.5%
9476
 
6.0%
4331
 
4.1%
7238
 
3.0%
Lowercase Letter
ValueCountFrequency (%)
r3129
20.5%
e3036
19.9%
y2943
19.3%
a2943
19.3%
s2943
19.3%
o186
 
1.2%
m93
 
0.6%
Dash Punctuation
ValueCountFrequency (%)
-2850
100.0%
Space Separator
ValueCountFrequency (%)
3129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin15273
52.2%
Common13968
47.8%

Most frequent character per script

Common
ValueCountFrequency (%)
3129
22.4%
-2850
20.4%
12111
15.1%
21042
 
7.5%
5904
 
6.5%
3874
 
6.3%
8809
 
5.8%
6684
 
4.9%
0520
 
3.7%
9476
 
3.4%
Other values (2)569
 
4.1%
Latin
ValueCountFrequency (%)
r3129
20.5%
e3036
19.9%
y2943
19.3%
a2943
19.3%
s2943
19.3%
o186
 
1.2%
m93
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII29241
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3129
10.7%
r3129
10.7%
e3036
10.4%
y2943
10.1%
a2943
10.1%
s2943
10.1%
-2850
9.7%
12111
7.2%
21042
 
3.6%
5904
 
3.1%
Other values (9)4211
14.4%

YearsCodingProf
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct11
Distinct (%)0.4%
Missing408
Missing (%)13.8%
Memory size23.1 KiB
3-5 years
791 
0-2 years
653 
6-8 years
401 
9-11 years
249 
12-14 years
139 
Other values (6)
305 

Length

Max length16
Median length9
Mean length9.52285264
Min length9

Characters and Unicode

Total characters24169
Distinct characters19
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3-5 years
2nd row18-20 years
3rd row6-8 years
4th row12-14 years
5th row0-2 years

Common Values

ValueCountFrequency (%)
3-5 years791
26.8%
0-2 years653
22.2%
6-8 years401
13.6%
9-11 years249
 
8.5%
12-14 years139
 
4.7%
15-17 years103
 
3.5%
18-20 years89
 
3.0%
21-23 years42
 
1.4%
30 or more years38
 
1.3%
24-26 years23
 
0.8%
(Missing)408
13.8%

Length

2021-06-21T11:44:07.025269image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
years2538
49.3%
3-5791
 
15.4%
0-2653
 
12.7%
6-8401
 
7.8%
9-11249
 
4.8%
12-14139
 
2.7%
15-17103
 
2.0%
18-2089
 
1.7%
21-2342
 
0.8%
more38
 
0.7%
Other values (4)109
 
2.1%

Most occurring characters

ValueCountFrequency (%)
2614
10.8%
r2614
10.8%
e2576
10.7%
y2538
10.5%
a2538
10.5%
s2538
10.5%
-2500
10.3%
11113
 
4.6%
21031
 
4.3%
5894
 
3.7%
Other values (9)3213
13.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter12918
53.4%
Decimal Number6137
25.4%
Space Separator2614
 
10.8%
Dash Punctuation2500
 
10.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
11113
18.1%
21031
16.8%
5894
14.6%
3871
14.2%
0780
12.7%
8490
8.0%
6424
 
6.9%
9259
 
4.2%
4162
 
2.6%
7113
 
1.8%
Lowercase Letter
ValueCountFrequency (%)
r2614
20.2%
e2576
19.9%
y2538
19.6%
a2538
19.6%
s2538
19.6%
o76
 
0.6%
m38
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-2500
100.0%
Space Separator
ValueCountFrequency (%)
2614
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin12918
53.4%
Common11251
46.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2614
23.2%
-2500
22.2%
11113
9.9%
21031
 
9.2%
5894
 
7.9%
3871
 
7.7%
0780
 
6.9%
8490
 
4.4%
6424
 
3.8%
9259
 
2.3%
Other values (2)275
 
2.4%
Latin
ValueCountFrequency (%)
r2614
20.2%
e2576
19.9%
y2538
19.6%
a2538
19.6%
s2538
19.6%
o76
 
0.6%
m38
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII24169
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2614
10.8%
r2614
10.8%
e2576
10.7%
y2538
10.5%
a2538
10.5%
s2538
10.5%
-2500
10.3%
11113
 
4.6%
21031
 
4.3%
5894
 
3.7%
Other values (9)3213
13.3%

HopeFiveYears
Categorical

HIGH CORRELATION
MISSING

Distinct7
Distinct (%)0.3%
Missing469
Missing (%)15.9%
Memory size23.1 KiB
Working in a different or more specialized technical role than the one I'm in now
872 
Working as a founder or co-founder of my own company
599 
Doing the same work
496 
Working as an engineering manager or other functional manager
251 
Working as a product manager or project manager
164 
Other values (2)
95 

Length

Max length81
Median length52
Mean length55.87928946
Min length10

Characters and Unicode

Total characters138413
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWorking as a founder or co-founder of my own company
2nd rowWorking in a different or more specialized technical role than the one I'm in now
3rd rowWorking as a founder or co-founder of my own company
4th rowWorking as a founder or co-founder of my own company
5th rowWorking in a different or more specialized technical role than the one I'm in now

Common Values

ValueCountFrequency (%)
Working in a different or more specialized technical role than the one I'm in now872
29.6%
Working as a founder or co-founder of my own company599
20.3%
Doing the same work496
16.8%
Working as an engineering manager or other functional manager251
 
8.5%
Working as a product manager or project manager164
 
5.6%
Working in a career completely unrelated to software development60
 
2.0%
Retirement35
 
1.2%
(Missing)469
15.9%

Length

2021-06-21T11:44:07.331803image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:07.430152image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
working1946
 
7.7%
or1886
 
7.5%
in1804
 
7.2%
a1695
 
6.7%
the1368
 
5.4%
as1014
 
4.0%
one872
 
3.5%
technical872
 
3.5%
i'm872
 
3.5%
now872
 
3.5%
Other values (28)11999
47.6%

Most occurring characters

ValueCountFrequency (%)
22723
16.4%
n13493
 
9.7%
o12976
 
9.4%
e12741
 
9.2%
r10077
 
7.3%
a8762
 
6.3%
i8522
 
6.2%
t5184
 
3.7%
c4513
 
3.3%
m4423
 
3.2%
Other values (20)34999
25.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter110870
80.1%
Space Separator22723
 
16.4%
Uppercase Letter3349
 
2.4%
Other Punctuation872
 
0.6%
Dash Punctuation599
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n13493
12.2%
o12976
11.7%
e12741
11.5%
r10077
 
9.1%
a8762
 
7.9%
i8522
 
7.7%
t5184
 
4.7%
c4513
 
4.1%
m4423
 
4.0%
f3852
 
3.5%
Other values (13)26327
23.7%
Uppercase Letter
ValueCountFrequency (%)
W1946
58.1%
I872
26.0%
D496
 
14.8%
R35
 
1.0%
Space Separator
ValueCountFrequency (%)
22723
100.0%
Dash Punctuation
ValueCountFrequency (%)
-599
100.0%
Other Punctuation
ValueCountFrequency (%)
'872
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin114219
82.5%
Common24194
 
17.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n13493
11.8%
o12976
11.4%
e12741
11.2%
r10077
 
8.8%
a8762
 
7.7%
i8522
 
7.5%
t5184
 
4.5%
c4513
 
4.0%
m4423
 
3.9%
f3852
 
3.4%
Other values (17)29676
26.0%
Common
ValueCountFrequency (%)
22723
93.9%
'872
 
3.6%
-599
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII138413
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22723
16.4%
n13493
 
9.7%
o12976
 
9.4%
e12741
 
9.2%
r10077
 
7.3%
a8762
 
6.3%
i8522
 
6.2%
t5184
 
3.7%
c4513
 
3.3%
m4423
 
3.2%
Other values (20)34999
25.3%

JobSearchStatus
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)0.1%
Missing435
Missing (%)14.8%
Memory size23.1 KiB
I�m not actively looking, but I am open to new opportunities
1542 
I am not interested in new job opportunities
645 
I am actively looking for a job
324 

Length

Max length60
Median length60
Mean length52.14814815
Min length31

Characters and Unicode

Total characters130944
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI�m not actively looking, but I am open to new opportunities
2nd rowI am actively looking for a job
3rd rowI�m not actively looking, but I am open to new opportunities
4th rowI�m not actively looking, but I am open to new opportunities
5th rowI�m not actively looking, but I am open to new opportunities

Common Values

ValueCountFrequency (%)
I�m not actively looking, but I am open to new opportunities1542
52.3%
I am not interested in new job opportunities645
21.9%
I am actively looking for a job324
 
11.0%
(Missing)435
 
14.8%

Length

2021-06-21T11:44:07.810645image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:07.917886image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
am2511
10.3%
i2511
10.3%
opportunities2187
9.0%
not2187
9.0%
new2187
9.0%
actively1866
7.7%
looking1866
7.7%
i�m1542
 
6.3%
open1542
 
6.3%
to1542
 
6.3%
Other values (6)4449
18.2%

Most occurring characters

ValueCountFrequency (%)
21879
16.7%
o14670
11.2%
t12801
 
9.8%
n11259
 
8.6%
e9717
 
7.4%
i9396
 
7.2%
p5916
 
4.5%
a4701
 
3.6%
I4053
 
3.1%
m4053
 
3.1%
Other values (16)32499
24.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter101928
77.8%
Space Separator21879
 
16.7%
Uppercase Letter4053
 
3.1%
Other Symbol1542
 
1.2%
Other Punctuation1542
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o14670
14.4%
t12801
12.6%
n11259
11.0%
e9717
9.5%
i9396
9.2%
p5916
 
5.8%
a4701
 
4.6%
m4053
 
4.0%
l3732
 
3.7%
u3729
 
3.7%
Other values (12)21954
21.5%
Uppercase Letter
ValueCountFrequency (%)
I4053
100.0%
Other Symbol
ValueCountFrequency (%)
1542
100.0%
Space Separator
ValueCountFrequency (%)
21879
100.0%
Other Punctuation
ValueCountFrequency (%)
,1542
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin105981
80.9%
Common24963
 
19.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o14670
13.8%
t12801
12.1%
n11259
10.6%
e9717
 
9.2%
i9396
 
8.9%
p5916
 
5.6%
a4701
 
4.4%
I4053
 
3.8%
m4053
 
3.8%
l3732
 
3.5%
Other values (13)25683
24.2%
Common
ValueCountFrequency (%)
21879
87.6%
1542
 
6.2%
,1542
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII129402
98.8%
Specials1542
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
21879
16.9%
o14670
11.3%
t12801
9.9%
n11259
 
8.7%
e9717
 
7.5%
i9396
 
7.3%
p5916
 
4.6%
a4701
 
3.6%
I4053
 
3.1%
m4053
 
3.1%
Other values (15)30957
23.9%
Specials
ValueCountFrequency (%)
1542
100.0%

LastNewJob
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)0.2%
Missing447
Missing (%)15.2%
Memory size23.1 KiB
Less than a year ago
895 
Between 1 and 2 years ago
585 
Between 2 and 4 years ago
528 
More than 4 years ago
488 
I've never had a job
 
3

Length

Max length25
Median length21
Mean length22.42216887
Min length20

Characters and Unicode

Total characters56033
Distinct characters24
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLess than a year ago
2nd rowMore than 4 years ago
3rd rowLess than a year ago
4th rowLess than a year ago
5th rowBetween 1 and 2 years ago

Common Values

ValueCountFrequency (%)
Less than a year ago895
30.4%
Between 1 and 2 years ago585
19.9%
Between 2 and 4 years ago528
17.9%
More than 4 years ago488
16.6%
I've never had a job3
 
0.1%
(Missing)447
15.2%

Length

2021-06-21T11:44:08.190394image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:08.293861image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
ago2496
18.3%
years1601
11.8%
than1383
10.2%
and1113
8.2%
between1113
8.2%
21113
8.2%
41016
7.5%
a898
 
6.6%
year895
 
6.6%
less895
 
6.6%
Other values (6)1085
8.0%

Most occurring characters

ValueCountFrequency (%)
11109
19.8%
a8389
15.0%
e7227
12.9%
n3612
 
6.4%
s3391
 
6.1%
r2987
 
5.3%
o2987
 
5.3%
t2496
 
4.5%
y2496
 
4.5%
g2496
 
4.5%
Other values (14)8843
15.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter39708
70.9%
Space Separator11109
 
19.8%
Decimal Number2714
 
4.8%
Uppercase Letter2499
 
4.5%
Other Punctuation3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a8389
21.1%
e7227
18.2%
n3612
9.1%
s3391
8.5%
r2987
 
7.5%
o2987
 
7.5%
t2496
 
6.3%
y2496
 
6.3%
g2496
 
6.3%
h1386
 
3.5%
Other values (5)2241
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B1113
44.5%
L895
35.8%
M488
19.5%
I3
 
0.1%
Decimal Number
ValueCountFrequency (%)
21113
41.0%
41016
37.4%
1585
21.6%
Space Separator
ValueCountFrequency (%)
11109
100.0%
Other Punctuation
ValueCountFrequency (%)
'3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin42207
75.3%
Common13826
 
24.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a8389
19.9%
e7227
17.1%
n3612
8.6%
s3391
8.0%
r2987
 
7.1%
o2987
 
7.1%
t2496
 
5.9%
y2496
 
5.9%
g2496
 
5.9%
h1386
 
3.3%
Other values (9)4740
11.2%
Common
ValueCountFrequency (%)
11109
80.3%
21113
 
8.1%
41016
 
7.3%
1585
 
4.2%
'3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII56033
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11109
19.8%
a8389
15.0%
e7227
12.9%
n3612
 
6.4%
s3391
 
6.1%
r2987
 
5.3%
o2987
 
5.3%
t2496
 
4.5%
y2496
 
4.5%
g2496
 
4.5%
Other values (14)8843
15.8%

UpdateCV
Categorical

HIGH CORRELATION
MISSING

Distinct8
Distinct (%)0.4%
Missing857
Missing (%)29.1%
Memory size23.1 KiB
My job status or other personal status changed
825 
A recruiter contacted me
300 
I had a negative experience or interaction at work
283 
A friend told me about a job opportunity
225 
I saw an employer�s advertisement
191 
Other values (3)
265 

Length

Max length64
Median length46
Mean length42.92819531
Min length24

Characters and Unicode

Total characters89677
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMy job status or other personal status changed
2nd rowI saw an employer�s advertisement
3rd rowA recruiter contacted me
4th rowMy job status or other personal status changed
5th rowI did not receive an expected change in compensation

Common Values

ValueCountFrequency (%)
My job status or other personal status changed825
28.0%
A recruiter contacted me300
 
10.2%
I had a negative experience or interaction at work283
 
9.6%
A friend told me about a job opportunity225
 
7.6%
I saw an employer�s advertisement191
 
6.5%
I did not receive an expected change in compensation149
 
5.1%
I received bad news about the future of my company or department109
 
3.7%
I received negative feedback on my job performance7
 
0.2%
(Missing)857
29.1%

Length

2021-06-21T11:44:08.632274image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:08.753113image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
status1650
 
10.4%
or1217
 
7.7%
job1057
 
6.7%
a1033
 
6.5%
my941
 
6.0%
other825
 
5.2%
personal825
 
5.2%
changed825
 
5.2%
i739
 
4.7%
me525
 
3.3%
Other values (34)6170
39.0%

Most occurring characters

ValueCountFrequency (%)
13718
15.3%
e9188
10.2%
t8438
 
9.4%
a6942
 
7.7%
o6669
 
7.4%
r5945
 
6.6%
n5156
 
5.7%
s4956
 
5.5%
c3126
 
3.5%
d2837
 
3.2%
Other values (19)22702
25.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter73679
82.2%
Space Separator13718
 
15.3%
Uppercase Letter2089
 
2.3%
Other Symbol191
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e9188
12.5%
t8438
11.5%
a6942
 
9.4%
o6669
 
9.1%
r5945
 
8.1%
n5156
 
7.0%
s4956
 
6.7%
c3126
 
4.2%
d2837
 
3.9%
i2792
 
3.8%
Other values (14)17630
23.9%
Uppercase Letter
ValueCountFrequency (%)
M825
39.5%
I739
35.4%
A525
25.1%
Space Separator
ValueCountFrequency (%)
13718
100.0%
Other Symbol
ValueCountFrequency (%)
191
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin75768
84.5%
Common13909
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e9188
12.1%
t8438
11.1%
a6942
 
9.2%
o6669
 
8.8%
r5945
 
7.8%
n5156
 
6.8%
s4956
 
6.5%
c3126
 
4.1%
d2837
 
3.7%
i2792
 
3.7%
Other values (17)19719
26.0%
Common
ValueCountFrequency (%)
13718
98.6%
191
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII89486
99.8%
Specials191
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
13718
15.3%
e9188
10.3%
t8438
 
9.4%
a6942
 
7.8%
o6669
 
7.5%
r5945
 
6.6%
n5156
 
5.8%
s4956
 
5.5%
c3126
 
3.5%
d2837
 
3.2%
Other values (18)22511
25.2%
Specials
ValueCountFrequency (%)
191
100.0%

CommunicationTools
Categorical

HIGH CARDINALITY
MISSING

Distinct348
Distinct (%)17.2%
Missing923
Missing (%)31.3%
Memory size23.1 KiB
Office / productivity suite (Microsoft Office, Google Suite, etc.)
 
136
Slack
 
113
Confluence;Jira;Slack
 
77
Other chat system (IRC, proprietary software, etc.)
 
53
Office / productivity suite (Microsoft Office, Google Suite, etc.);Slack
 
48
Other values (343)
1596 

Length

Max length271
Median length67
Mean length72.18783984
Min length4

Characters and Unicode

Total characters146036
Distinct characters41
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)7.9%

Sample

1st rowSlack
2nd rowConfluence;Office / productivity suite (Microsoft Office, Google Suite, etc.);Slack;Other wiki tool (Github, Google Sites, proprietary software, etc.)
3rd rowOffice / productivity suite (Microsoft Office, Google Suite, etc.)
4th rowConfluence;Jira;Office / productivity suite (Microsoft Office, Google Suite, etc.);Other chat system (IRC, proprietary software, etc.)
5th rowConfluence;Office / productivity suite (Microsoft Office, Google Suite, etc.);Stack Overflow Enterprise;Other chat system (IRC, proprietary software, etc.);Other wiki tool (Github, Google Sites, proprietary software, etc.)

Common Values

ValueCountFrequency (%)
Office / productivity suite (Microsoft Office, Google Suite, etc.)136
 
4.6%
Slack113
 
3.8%
Confluence;Jira;Slack77
 
2.6%
Other chat system (IRC, proprietary software, etc.)53
 
1.8%
Office / productivity suite (Microsoft Office, Google Suite, etc.);Slack48
 
1.6%
Slack;Trello46
 
1.6%
Jira;Slack44
 
1.5%
Slack;Other wiki tool (Github, Google Sites, proprietary software, etc.)41
 
1.4%
Confluence;Jira40
 
1.4%
Confluence;Jira;Office / productivity suite (Microsoft Office, Google Suite, etc.);Slack38
 
1.3%
Other values (338)1387
47.1%
(Missing)923
31.3%

Length

2021-06-21T11:44:09.211496image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
google1637
 
10.1%
suite1612
 
10.0%
office1145
 
7.1%
etc1085
 
6.7%
software998
 
6.2%
proprietary998
 
6.2%
806
 
5.0%
microsoft806
 
5.0%
productivity806
 
5.0%
wiki581
 
3.6%
Other values (151)5703
35.3%

Most occurring characters

ValueCountFrequency (%)
14154
 
9.7%
e12825
 
8.8%
t12521
 
8.6%
o11047
 
7.6%
i10039
 
6.9%
r8021
 
5.5%
c7374
 
5.0%
f5725
 
3.9%
a5576
 
3.8%
l4837
 
3.3%
Other values (31)53917
36.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter104696
71.7%
Space Separator14154
 
9.7%
Uppercase Letter12854
 
8.8%
Other Punctuation10724
 
7.3%
Open Punctuation1804
 
1.2%
Close Punctuation1804
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e12825
12.2%
t12521
12.0%
o11047
10.6%
i10039
9.6%
r8021
 
7.7%
c7374
 
7.0%
f5725
 
5.5%
a5576
 
5.3%
l4837
 
4.6%
s4517
 
4.3%
Other values (12)22214
21.2%
Uppercase Letter
ValueCountFrequency (%)
O2674
20.8%
S2499
19.4%
G2396
18.6%
C1610
12.5%
J879
 
6.8%
M806
 
6.3%
H560
 
4.4%
I417
 
3.2%
R417
 
3.2%
T348
 
2.7%
Other values (2)248
 
1.9%
Other Punctuation
ValueCountFrequency (%)
,4189
39.1%
;3497
32.6%
.1804
16.8%
/1234
 
11.5%
Space Separator
ValueCountFrequency (%)
14154
100.0%
Open Punctuation
ValueCountFrequency (%)
(1804
100.0%
Close Punctuation
ValueCountFrequency (%)
)1804
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin117550
80.5%
Common28486
 
19.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e12825
 
10.9%
t12521
 
10.7%
o11047
 
9.4%
i10039
 
8.5%
r8021
 
6.8%
c7374
 
6.3%
f5725
 
4.9%
a5576
 
4.7%
l4837
 
4.1%
s4517
 
3.8%
Other values (24)35068
29.8%
Common
ValueCountFrequency (%)
14154
49.7%
,4189
 
14.7%
;3497
 
12.3%
(1804
 
6.3%
.1804
 
6.3%
)1804
 
6.3%
/1234
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII146036
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14154
 
9.7%
e12825
 
8.8%
t12521
 
8.6%
o11047
 
7.6%
i10039
 
6.9%
r8021
 
5.5%
c7374
 
5.0%
f5725
 
3.9%
a5576
 
3.8%
l4837
 
3.3%
Other values (31)53917
36.9%

TimeFullyProductive
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)0.3%
Missing894
Missing (%)30.3%
Memory size23.1 KiB
One to three months
909 
Less than a month
643 
Three to six months
347 
Six to nine months
111 
Nine months to a year
 
25

Length

Max length21
Median length19
Mean length18.31871345
Min length16

Characters and Unicode

Total characters37590
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOne to three months
2nd rowOne to three months
3rd rowThree to six months
4th rowThree to six months
5th rowLess than a month

Common Values

ValueCountFrequency (%)
One to three months909
30.9%
Less than a month643
21.8%
Three to six months347
 
11.8%
Six to nine months111
 
3.8%
Nine months to a year25
 
0.8%
More than a year17
 
0.6%
(Missing)894
30.3%

Length

2021-06-21T11:44:09.503128image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:09.602620image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
to1392
16.9%
months1392
16.9%
three1256
15.3%
one909
11.0%
a685
8.3%
than660
8.0%
less643
7.8%
month643
7.8%
six458
 
5.6%
nine136
 
1.7%
Other values (2)59
 
0.7%

Most occurring characters

ValueCountFrequency (%)
6181
16.4%
t4996
13.3%
e4259
11.3%
h3951
10.5%
n3851
10.2%
o3444
9.2%
s3025
8.0%
m2035
 
5.4%
a1387
 
3.7%
r1315
 
3.5%
Other values (9)3146
8.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter29357
78.1%
Space Separator6181
 
16.4%
Uppercase Letter2052
 
5.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t4996
17.0%
e4259
14.5%
h3951
13.5%
n3851
13.1%
o3444
11.7%
s3025
10.3%
m2035
6.9%
a1387
 
4.7%
r1315
 
4.5%
i594
 
2.0%
Other values (2)500
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
O909
44.3%
L643
31.3%
T347
 
16.9%
S111
 
5.4%
N25
 
1.2%
M17
 
0.8%
Space Separator
ValueCountFrequency (%)
6181
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin31409
83.6%
Common6181
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
t4996
15.9%
e4259
13.6%
h3951
12.6%
n3851
12.3%
o3444
11.0%
s3025
9.6%
m2035
6.5%
a1387
 
4.4%
r1315
 
4.2%
O909
 
2.9%
Other values (8)2237
7.1%
Common
ValueCountFrequency (%)
6181
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII37590
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6181
16.4%
t4996
13.3%
e4259
11.3%
h3951
10.5%
n3851
10.2%
o3444
9.2%
s3025
8.0%
m2035
 
5.4%
a1387
 
3.7%
r1315
 
3.5%
Other values (9)3146
8.4%

EducationTypes
Categorical

HIGH CARDINALITY
MISSING

Distinct264
Distinct (%)12.4%
Missing818
Missing (%)27.8%
Memory size23.1 KiB
Taught yourself a new language, framework, or tool without taking a formal course
179 
Taken an online course in programming or software development (e.g. a MOOC);Taught yourself a new language, framework, or tool without taking a formal course
 
144
Taught yourself a new language, framework, or tool without taking a formal course;Contributed to open source software
 
124
Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course
 
78
Taken an online course in programming or software development (e.g. a MOOC);Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course
 
68
Other values (259)
1535 

Length

Max length552
Median length193
Mean length199.5592105
Min length27

Characters and Unicode

Total characters424662
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)3.8%

Sample

1st rowTaught yourself a new language, framework, or tool without taking a formal course;Participated in a hackathon
2nd rowTaught yourself a new language, framework, or tool without taking a formal course;Contributed to open source software
3rd rowCompleted an industry certification program (e.g. MCPD);Taught yourself a new language, framework, or tool without taking a formal course
4th rowTaken a part-time in-person course in programming or software development;Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course
5th rowReceived on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course;Participated in online coding competitions (e.g. HackerRank, CodeChef, TopCoder)

Common Values

ValueCountFrequency (%)
Taught yourself a new language, framework, or tool without taking a formal course179
 
6.1%
Taken an online course in programming or software development (e.g. a MOOC);Taught yourself a new language, framework, or tool without taking a formal course144
 
4.9%
Taught yourself a new language, framework, or tool without taking a formal course;Contributed to open source software124
 
4.2%
Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course78
 
2.6%
Taken an online course in programming or software development (e.g. a MOOC);Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course68
 
2.3%
Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course;Contributed to open source software53
 
1.8%
Taken an online course in programming or software development (e.g. a MOOC);Taught yourself a new language, framework, or tool without taking a formal course;Contributed to open source software49
 
1.7%
Taken an online course in programming or software development (e.g. a MOOC);Taught yourself a new language, framework, or tool without taking a formal course;Participated in a hackathon;Contributed to open source software37
 
1.3%
Taken an online course in programming or software development (e.g. a MOOC);Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course;Contributed to open source software34
 
1.2%
Taken an online course in programming or software development (e.g. a MOOC);Taught yourself a new language, framework, or tool without taking a formal course;Participated in online coding competitions (e.g. HackerRank, CodeChef, TopCoder)34
 
1.2%
Other values (254)1328
45.1%
(Missing)818
27.8%

Length

2021-06-21T11:44:10.133124image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
a6001
 
10.6%
in3629
 
6.4%
or3510
 
6.2%
software3094
 
5.5%
course2110
 
3.7%
e.g1896
 
3.3%
framework1857
 
3.3%
formal1857
 
3.3%
new1857
 
3.3%
without1857
 
3.3%
Other values (60)28979
51.2%

Most occurring characters

ValueCountFrequency (%)
54519
12.8%
e37841
 
8.9%
o37326
 
8.8%
a32041
 
7.5%
r28002
 
6.6%
n26993
 
6.4%
t25939
 
6.1%
i20666
 
4.9%
g14281
 
3.4%
u12961
 
3.1%
Other values (28)134093
31.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter335407
79.0%
Space Separator54519
 
12.8%
Uppercase Letter15284
 
3.6%
Other Punctuation13078
 
3.1%
Dash Punctuation2582
 
0.6%
Open Punctuation1896
 
0.4%
Close Punctuation1896
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e37841
11.3%
o37326
11.1%
a32041
 
9.6%
r28002
 
8.3%
n26993
 
8.0%
t25939
 
7.7%
i20666
 
6.2%
g14281
 
4.3%
u12961
 
3.9%
l12263
 
3.7%
Other values (13)87094
26.0%
Uppercase Letter
ValueCountFrequency (%)
C4110
26.9%
T3800
24.9%
O2126
13.9%
P1701
11.1%
M1372
 
9.0%
R1342
 
8.8%
H524
 
3.4%
D309
 
2.0%
Other Punctuation
ValueCountFrequency (%)
,4762
36.4%
;4524
34.6%
.3792
29.0%
Space Separator
ValueCountFrequency (%)
54519
100.0%
Open Punctuation
ValueCountFrequency (%)
(1896
100.0%
Close Punctuation
ValueCountFrequency (%)
)1896
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2582
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin350691
82.6%
Common73971
 
17.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e37841
 
10.8%
o37326
 
10.6%
a32041
 
9.1%
r28002
 
8.0%
n26993
 
7.7%
t25939
 
7.4%
i20666
 
5.9%
g14281
 
4.1%
u12961
 
3.7%
l12263
 
3.5%
Other values (21)102378
29.2%
Common
ValueCountFrequency (%)
54519
73.7%
,4762
 
6.4%
;4524
 
6.1%
.3792
 
5.1%
-2582
 
3.5%
(1896
 
2.6%
)1896
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII424662
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
54519
12.8%
e37841
 
8.9%
o37326
 
8.8%
a32041
 
7.5%
r28002
 
6.6%
n26993
 
6.4%
t25939
 
6.1%
i20666
 
4.9%
g14281
 
3.4%
u12961
 
3.1%
Other values (28)134093
31.6%

SelfTaughtTypes
Categorical

HIGH CARDINALITY
MISSING

Distinct226
Distinct (%)12.5%
Missing1134
Missing (%)38.5%
Memory size23.1 KiB
The official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow
 
113
The official documentation and/or standards for the technology;Questions & answers on Stack Overflow
 
109
The official documentation and/or standards for the technology;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)
 
103
The official documentation and/or standards for the technology;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.);The technology�s online help system
 
95
The official documentation and/or standards for the technology;Questions & answers on Stack Overflow;The technology�s online help system
 
87
Other values (221)
1305 

Length

Max length593
Median length212
Mean length226.6445916
Min length35

Characters and Unicode

Total characters410680
Distinct characters43
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)5.0%

Sample

1st rowThe official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)
2nd rowThe official documentation and/or standards for the technology;Questions & answers on Stack Overflow
3rd rowThe official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow;The technology�s online help system
4th rowThe official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow
5th rowThe official documentation and/or standards for the technology;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)

Common Values

ValueCountFrequency (%)
The official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow113
 
3.8%
The official documentation and/or standards for the technology;Questions & answers on Stack Overflow109
 
3.7%
The official documentation and/or standards for the technology;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)103
 
3.5%
The official documentation and/or standards for the technology;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.);The technology�s online help system95
 
3.2%
The official documentation and/or standards for the technology;Questions & answers on Stack Overflow;The technology�s online help system87
 
3.0%
The official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow;The technology�s online help system77
 
2.6%
The official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.);The technology�s online help system73
 
2.5%
The official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)62
 
2.1%
The official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;A college/university computer science or software engineering book;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.);The technology�s online help system36
 
1.2%
The official documentation and/or standards for the technology28
 
1.0%
Other values (216)1029
34.9%
(Missing)1134
38.5%

Length

2021-06-21T11:44:10.483355image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
the3414
 
6.3%
or2641
 
4.9%
stack2428
 
4.5%
documentation1817
 
3.3%
for1817
 
3.3%
official1522
 
2.8%
and/or1522
 
2.8%
standards1522
 
2.8%
1514
 
2.8%
on1514
 
2.8%
Other values (91)34562
63.7%

Most occurring characters

ValueCountFrequency (%)
52461
 
12.8%
e37370
 
9.1%
o35481
 
8.6%
n25951
 
6.3%
s24497
 
6.0%
r22907
 
5.6%
t21726
 
5.3%
i18739
 
4.6%
a18001
 
4.4%
l17584
 
4.3%
Other values (33)135963
33.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter320068
77.9%
Space Separator52461
 
12.8%
Uppercase Letter17457
 
4.3%
Other Punctuation16106
 
3.9%
Other Symbol1762
 
0.4%
Dash Punctuation998
 
0.2%
Open Punctuation914
 
0.2%
Close Punctuation914
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e37370
11.7%
o35481
11.1%
n25951
 
8.1%
s24497
 
7.7%
r22907
 
7.2%
t21726
 
6.8%
i18739
 
5.9%
a18001
 
5.6%
l17584
 
5.5%
c13378
 
4.2%
Other values (13)84434
26.4%
Uppercase Letter
ValueCountFrequency (%)
O4264
24.4%
T2727
15.6%
S2428
13.9%
A2194
12.6%
R1836
10.5%
Q1514
 
8.7%
I1209
 
6.9%
C914
 
5.2%
W295
 
1.7%
P76
 
0.4%
Other Punctuation
ValueCountFrequency (%)
,5906
36.7%
;4986
31.0%
/1872
 
11.6%
.1828
 
11.3%
&1514
 
9.4%
Space Separator
ValueCountFrequency (%)
52461
100.0%
Dash Punctuation
ValueCountFrequency (%)
-998
100.0%
Other Symbol
ValueCountFrequency (%)
1762
100.0%
Open Punctuation
ValueCountFrequency (%)
(914
100.0%
Close Punctuation
ValueCountFrequency (%)
)914
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin337525
82.2%
Common73155
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e37370
 
11.1%
o35481
 
10.5%
n25951
 
7.7%
s24497
 
7.3%
r22907
 
6.8%
t21726
 
6.4%
i18739
 
5.6%
a18001
 
5.3%
l17584
 
5.2%
c13378
 
4.0%
Other values (23)101891
30.2%
Common
ValueCountFrequency (%)
52461
71.7%
,5906
 
8.1%
;4986
 
6.8%
/1872
 
2.6%
.1828
 
2.5%
1762
 
2.4%
&1514
 
2.1%
-998
 
1.4%
(914
 
1.2%
)914
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII408918
99.6%
Specials1762
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52461
 
12.8%
e37370
 
9.1%
o35481
 
8.7%
n25951
 
6.3%
s24497
 
6.0%
r22907
 
5.6%
t21726
 
5.3%
i18739
 
4.6%
a18001
 
4.4%
l17584
 
4.3%
Other values (32)134201
32.8%
Specials
ValueCountFrequency (%)
1762
100.0%

TimeAfterBootcamp
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct8
Distinct (%)3.6%
Missing2725
Missing (%)92.5%
Memory size23.1 KiB
I already had a full-time job as a developer when I began the program
112 
Immediately after graduating
36 
One to three months
25 
Less than a month
19 
Four to six months
 
11
Other values (3)
18 

Length

Max length69
Median length69
Mean length45.83710407
Min length17

Characters and Unicode

Total characters10130
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowImmediately after graduating
2nd rowI already had a full-time job as a developer when I began the program
3rd rowImmediately after graduating
4th rowI already had a full-time job as a developer when I began the program
5th rowI already had a full-time job as a developer when I began the program

Common Values

ValueCountFrequency (%)
I already had a full-time job as a developer when I began the program112
 
3.8%
Immediately after graduating36
 
1.2%
One to three months25
 
0.8%
Less than a month19
 
0.6%
Four to six months11
 
0.4%
Six months to a year9
 
0.3%
Longer than a year5
 
0.2%
I haven�t gotten a developer job4
 
0.1%
(Missing)2725
92.5%

Length

2021-06-21T11:44:10.803291image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:10.902996image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
a261
13.1%
i228
 
11.5%
job116
 
5.8%
developer116
 
5.8%
as112
 
5.6%
already112
 
5.6%
program112
 
5.6%
full-time112
 
5.6%
had112
 
5.6%
when112
 
5.6%
Other values (18)592
29.8%

Most occurring characters

ValueCountFrequency (%)
1764
17.4%
e1137
11.2%
a1119
 
11.0%
r579
 
5.7%
t502
 
5.0%
l488
 
4.8%
o473
 
4.7%
h453
 
4.5%
d412
 
4.1%
n386
 
3.8%
Other values (20)2817
27.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter7917
78.2%
Space Separator1764
 
17.4%
Uppercase Letter333
 
3.3%
Dash Punctuation112
 
1.1%
Other Symbol4
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e1137
14.4%
a1119
14.1%
r579
 
7.3%
t502
 
6.3%
l488
 
6.2%
o473
 
6.0%
h453
 
5.7%
d412
 
5.2%
n386
 
4.9%
m360
 
4.5%
Other values (12)2008
25.4%
Uppercase Letter
ValueCountFrequency (%)
I264
79.3%
O25
 
7.5%
L24
 
7.2%
F11
 
3.3%
S9
 
2.7%
Space Separator
ValueCountFrequency (%)
1764
100.0%
Dash Punctuation
ValueCountFrequency (%)
-112
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8250
81.4%
Common1880
 
18.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e1137
13.8%
a1119
13.6%
r579
 
7.0%
t502
 
6.1%
l488
 
5.9%
o473
 
5.7%
h453
 
5.5%
d412
 
5.0%
n386
 
4.7%
m360
 
4.4%
Other values (17)2341
28.4%
Common
ValueCountFrequency (%)
1764
93.8%
-112
 
6.0%
4
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII10126
> 99.9%
Specials4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1764
17.4%
e1137
11.2%
a1119
 
11.1%
r579
 
5.7%
t502
 
5.0%
l488
 
4.8%
o473
 
4.7%
h453
 
4.5%
d412
 
4.1%
n386
 
3.8%
Other values (19)2813
27.8%
Specials
ValueCountFrequency (%)
4
100.0%

HackathonReasons
Categorical

HIGH CARDINALITY
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct98
Distinct (%)11.5%
Missing2097
Missing (%)71.2%
Memory size23.1 KiB
To improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;Because I find it enjoyable
113 
Because I find it enjoyable
105 
To improve my general technical skills or programming ability;Because I find it enjoyable
67 
To improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;To improve my ability to work on a team with other programmers;Because I find it enjoyable
 
32
To improve my general technical skills or programming ability
 
29
Other values (93)
503 

Length

Max length343
Median length152
Mean length146.6242638
Min length27

Characters and Unicode

Total characters124484
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)1.8%

Sample

1st rowTo build my professional network
2nd rowTo improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;Because I find it enjoyable
3rd rowTo improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;To improve my ability to work on a team with other programmers;Because I find it enjoyable
4th rowBecause I find it enjoyable
5th rowTo improve my general technical skills or programming ability

Common Values

ValueCountFrequency (%)
To improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;Because I find it enjoyable113
 
3.8%
Because I find it enjoyable105
 
3.6%
To improve my general technical skills or programming ability;Because I find it enjoyable67
 
2.3%
To improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;To improve my ability to work on a team with other programmers;Because I find it enjoyable32
 
1.1%
To improve my general technical skills or programming ability29
 
1.0%
To improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;To improve my ability to work on a team with other programmers;To build my professional network;Because I find it enjoyable23
 
0.8%
To improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology21
 
0.7%
To improve my knowledge of a specific programming language, framework, or other technology;Because I find it enjoyable17
 
0.6%
To improve my knowledge of a specific programming language, framework, or other technology17
 
0.6%
To improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;To improve my ability to work on a team with other programmers;To build my professional network;To help me find new job opportunities;To win prizes or cash awards;Because I find it enjoyable16
 
0.5%
Other values (88)409
 
13.9%
(Missing)2097
71.2%

Length

2021-06-21T11:44:11.340046image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
my1444
 
7.8%
improve1209
 
6.6%
or1142
 
6.2%
to977
 
5.3%
programming976
 
5.3%
find836
 
4.5%
a658
 
3.6%
other658
 
3.6%
i652
 
3.5%
it652
 
3.5%
Other values (40)9198
50.0%

Most occurring characters

ValueCountFrequency (%)
17553
14.1%
o10745
 
8.6%
e10516
 
8.4%
i8596
 
6.9%
r8280
 
6.7%
a7298
 
5.9%
n6078
 
4.9%
m5913
 
4.8%
l5569
 
4.5%
g4436
 
3.6%
Other values (20)39500
31.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter101386
81.4%
Space Separator17553
 
14.1%
Uppercase Letter3098
 
2.5%
Other Punctuation2447
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o10745
 
10.6%
e10516
 
10.4%
i8596
 
8.5%
r8280
 
8.2%
a7298
 
7.2%
n6078
 
6.0%
m5913
 
5.8%
l5569
 
5.5%
g4436
 
4.4%
t4372
 
4.3%
Other values (14)29583
29.2%
Uppercase Letter
ValueCountFrequency (%)
T1794
57.9%
B652
 
21.0%
I652
 
21.0%
Other Punctuation
ValueCountFrequency (%)
;1597
65.3%
,850
34.7%
Space Separator
ValueCountFrequency (%)
17553
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin104484
83.9%
Common20000
 
16.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o10745
 
10.3%
e10516
 
10.1%
i8596
 
8.2%
r8280
 
7.9%
a7298
 
7.0%
n6078
 
5.8%
m5913
 
5.7%
l5569
 
5.3%
g4436
 
4.2%
t4372
 
4.2%
Other values (17)32681
31.3%
Common
ValueCountFrequency (%)
17553
87.8%
;1597
 
8.0%
,850
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII124484
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
17553
14.1%
o10745
 
8.6%
e10516
 
8.4%
i8596
 
6.9%
r8280
 
6.7%
a7298
 
5.9%
n6078
 
4.9%
m5913
 
4.8%
l5569
 
4.5%
g4436
 
3.6%
Other values (20)39500
31.7%

AgreeDisagree1
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)0.2%
Missing813
Missing (%)27.6%
Memory size23.1 KiB
Agree
1166 
Neither Agree nor Disagree
418 
Strongly agree
382 
Disagree
126 
Strongly disagree
 
41

Length

Max length26
Median length5
Mean length11.1350211
Min length5

Characters and Unicode

Total characters23751
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowStrongly agree
2nd rowAgree
3rd rowDisagree
4th rowStrongly agree
5th rowDisagree

Common Values

ValueCountFrequency (%)
Agree1166
39.6%
Neither Agree nor Disagree418
 
14.2%
Strongly agree382
 
13.0%
Disagree126
 
4.3%
Strongly disagree41
 
1.4%
(Missing)813
27.6%

Length

2021-06-21T11:44:11.657835image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:11.754588image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
agree1966
51.6%
disagree585
 
15.4%
strongly423
 
11.1%
nor418
 
11.0%
neither418
 
11.0%

Most occurring characters

ValueCountFrequency (%)
e5938
25.0%
r3810
16.0%
g2974
12.5%
1677
 
7.1%
A1584
 
6.7%
i1003
 
4.2%
a967
 
4.1%
t841
 
3.5%
o841
 
3.5%
n841
 
3.5%
Other values (8)3275
13.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter19105
80.4%
Uppercase Letter2969
 
12.5%
Space Separator1677
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e5938
31.1%
r3810
19.9%
g2974
15.6%
i1003
 
5.2%
a967
 
5.1%
t841
 
4.4%
o841
 
4.4%
n841
 
4.4%
s585
 
3.1%
l423
 
2.2%
Other values (3)882
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
A1584
53.4%
D544
 
18.3%
S423
 
14.2%
N418
 
14.1%
Space Separator
ValueCountFrequency (%)
1677
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin22074
92.9%
Common1677
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e5938
26.9%
r3810
17.3%
g2974
13.5%
A1584
 
7.2%
i1003
 
4.5%
a967
 
4.4%
t841
 
3.8%
o841
 
3.8%
n841
 
3.8%
s585
 
2.7%
Other values (7)2690
12.2%
Common
ValueCountFrequency (%)
1677
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII23751
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e5938
25.0%
r3810
16.0%
g2974
12.5%
1677
 
7.1%
A1584
 
6.7%
i1003
 
4.2%
a967
 
4.1%
t841
 
3.5%
o841
 
3.5%
n841
 
3.5%
Other values (8)3275
13.8%

AgreeDisagree2
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)0.2%
Missing813
Missing (%)27.6%
Memory size23.1 KiB
Agree
575 
Neither Agree nor Disagree
567 
Disagree
563 
Strongly disagree
268 
Strongly agree
160 

Length

Max length26
Median length8
Mean length13.55696203
Min length5

Characters and Unicode

Total characters28917
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowStrongly agree
2nd rowAgree
3rd rowDisagree
4th rowAgree
5th rowNeither Agree nor Disagree

Common Values

ValueCountFrequency (%)
Agree575
19.5%
Neither Agree nor Disagree567
19.2%
Disagree563
19.1%
Strongly disagree268
 
9.1%
Strongly agree160
 
5.4%
(Missing)813
27.6%

Length

2021-06-21T11:44:12.030418image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:12.112783image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
disagree1398
32.8%
agree1302
30.5%
nor567
13.3%
neither567
13.3%
strongly428
 
10.0%

Most occurring characters

ValueCountFrequency (%)
e6534
22.6%
r4262
14.7%
g3128
10.8%
2129
 
7.4%
i1965
 
6.8%
a1558
 
5.4%
s1398
 
4.8%
A1142
 
3.9%
D1130
 
3.9%
t995
 
3.4%
Other values (8)4676
16.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter23521
81.3%
Uppercase Letter3267
 
11.3%
Space Separator2129
 
7.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e6534
27.8%
r4262
18.1%
g3128
13.3%
i1965
 
8.4%
a1558
 
6.6%
s1398
 
5.9%
t995
 
4.2%
o995
 
4.2%
n995
 
4.2%
h567
 
2.4%
Other values (3)1124
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
A1142
35.0%
D1130
34.6%
N567
17.4%
S428
 
13.1%
Space Separator
ValueCountFrequency (%)
2129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin26788
92.6%
Common2129
 
7.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e6534
24.4%
r4262
15.9%
g3128
11.7%
i1965
 
7.3%
a1558
 
5.8%
s1398
 
5.2%
A1142
 
4.3%
D1130
 
4.2%
t995
 
3.7%
o995
 
3.7%
Other values (7)3681
13.7%
Common
ValueCountFrequency (%)
2129
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII28917
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e6534
22.6%
r4262
14.7%
g3128
10.8%
2129
 
7.4%
i1965
 
6.8%
a1558
 
5.4%
s1398
 
4.8%
A1142
 
3.9%
D1130
 
3.9%
t995
 
3.4%
Other values (8)4676
16.2%

AgreeDisagree3
Categorical

HIGH CORRELATION
MISSING

Distinct5
Distinct (%)0.2%
Missing807
Missing (%)27.4%
Memory size23.1 KiB
Disagree
766 
Neither Agree nor Disagree
512 
Strongly disagree
496 
Agree
298 
Strongly agree
 
67

Length

Max length26
Median length14
Mean length14.1654979
Min length5

Characters and Unicode

Total characters30300
Distinct characters18
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNeither Agree nor Disagree
2nd rowNeither Agree nor Disagree
3rd rowStrongly disagree
4th rowStrongly disagree
5th rowStrongly disagree

Common Values

ValueCountFrequency (%)
Disagree766
26.0%
Neither Agree nor Disagree512
17.4%
Strongly disagree496
16.8%
Agree298
 
10.1%
Strongly agree67
 
2.3%
(Missing)807
27.4%

Length

2021-06-21T11:44:12.430566image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:12.523425image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
disagree1774
41.9%
agree877
20.7%
strongly563
 
13.3%
nor512
 
12.1%
neither512
 
12.1%

Most occurring characters

ValueCountFrequency (%)
e6326
20.9%
r4238
14.0%
g3214
10.6%
i2286
 
7.5%
2099
 
6.9%
a1841
 
6.1%
s1774
 
5.9%
D1278
 
4.2%
t1075
 
3.5%
n1075
 
3.5%
Other values (8)5094
16.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter25038
82.6%
Uppercase Letter3163
 
10.4%
Space Separator2099
 
6.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e6326
25.3%
r4238
16.9%
g3214
12.8%
i2286
 
9.1%
a1841
 
7.4%
s1774
 
7.1%
t1075
 
4.3%
n1075
 
4.3%
o1075
 
4.3%
l563
 
2.2%
Other values (3)1571
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
D1278
40.4%
A810
25.6%
S563
17.8%
N512
16.2%
Space Separator
ValueCountFrequency (%)
2099
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin28201
93.1%
Common2099
 
6.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e6326
22.4%
r4238
15.0%
g3214
11.4%
i2286
 
8.1%
a1841
 
6.5%
s1774
 
6.3%
D1278
 
4.5%
t1075
 
3.8%
n1075
 
3.8%
o1075
 
3.8%
Other values (7)4019
14.3%
Common
ValueCountFrequency (%)
2099
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII30300
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e6326
20.9%
r4238
14.0%
g3214
10.6%
i2286
 
7.5%
2099
 
6.9%
a1841
 
6.1%
s1774
 
5.9%
D1278
 
4.2%
t1075
 
3.5%
n1075
 
3.5%
Other values (8)5094
16.8%

LanguageWorkedWith
Categorical

HIGH CARDINALITY
MISSING

Distinct1578
Distinct (%)64.5%
Missing499
Missing (%)16.9%
Memory size23.1 KiB
C#;JavaScript;SQL;HTML;CSS
 
55
JavaScript;PHP;SQL;HTML;CSS
 
42
C#;JavaScript;SQL;TypeScript;HTML;CSS
 
35
Java
 
31
JavaScript;HTML;CSS
 
28
Other values (1573)
2256 

Length

Max length147
Median length35
Mean length36.90273805
Min length1

Characters and Unicode

Total characters90301
Distinct characters50
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1330 ?
Unique (%)54.4%

Sample

1st rowJavaScript;Python;HTML;CSS
2nd rowJavaScript;Python;Bash/Shell
3rd rowC#;JavaScript;SQL;TypeScript;HTML;CSS;Bash/Shell
4th rowC;C++;Java;Matlab;R;SQL;Bash/Shell
5th rowJava;JavaScript;Python;TypeScript;HTML;CSS

Common Values

ValueCountFrequency (%)
C#;JavaScript;SQL;HTML;CSS55
 
1.9%
JavaScript;PHP;SQL;HTML;CSS42
 
1.4%
C#;JavaScript;SQL;TypeScript;HTML;CSS35
 
1.2%
Java31
 
1.1%
JavaScript;HTML;CSS28
 
1.0%
JavaScript;PHP;HTML;CSS26
 
0.9%
JavaScript;PHP;SQL;HTML;CSS;Bash/Shell19
 
0.6%
Java;JavaScript;SQL;HTML;CSS18
 
0.6%
C#;JavaScript;TypeScript;HTML;CSS18
 
0.6%
JavaScript;TypeScript;HTML;CSS17
 
0.6%
Other values (1568)2158
73.3%
(Missing)499
 
16.9%

Length

2021-06-21T11:44:12.897673image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
basic99
 
3.7%
c#;javascript;sql;html;css55
 
2.0%
6;html;css45
 
1.7%
javascript;php;sql;html;css42
 
1.6%
c#;javascript;sql;typescript;html;css35
 
1.3%
java31
 
1.1%
javascript;html;css28
 
1.0%
javascript;php;html;css26
 
1.0%
6;html;css;bash/shell24
 
0.9%
c21
 
0.8%
Other values (1577)2293
85.0%

Most occurring characters

ValueCountFrequency (%)
;12476
 
13.8%
S8165
 
9.0%
a7460
 
8.3%
t3904
 
4.3%
C3769
 
4.2%
L3172
 
3.5%
v3073
 
3.4%
i3048
 
3.4%
l2890
 
3.2%
h2861
 
3.2%
Other values (40)39483
43.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter42214
46.7%
Uppercase Letter31909
35.3%
Other Punctuation14553
 
16.1%
Math Symbol1098
 
1.2%
Space Separator252
 
0.3%
Dash Punctuation176
 
0.2%
Decimal Number99
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a7460
17.7%
t3904
9.2%
v3073
 
7.3%
i3048
 
7.2%
l2890
 
6.8%
h2861
 
6.8%
p2813
 
6.7%
c2800
 
6.6%
r2544
 
6.0%
e2377
 
5.6%
Other values (12)8444
20.0%
Uppercase Letter
ValueCountFrequency (%)
S8165
25.6%
C3769
11.8%
L3172
 
9.9%
J2799
 
8.8%
P2521
 
7.9%
H2439
 
7.6%
T2296
 
7.2%
M1761
 
5.5%
Q1451
 
4.5%
B1333
 
4.2%
Other values (10)2203
 
6.9%
Other Punctuation
ValueCountFrequency (%)
;12476
85.7%
/1010
 
6.9%
#897
 
6.2%
.170
 
1.2%
Math Symbol
ValueCountFrequency (%)
+1098
100.0%
Dash Punctuation
ValueCountFrequency (%)
-176
100.0%
Space Separator
ValueCountFrequency (%)
252
100.0%
Decimal Number
ValueCountFrequency (%)
699
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin74123
82.1%
Common16178
 
17.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
S8165
 
11.0%
a7460
 
10.1%
t3904
 
5.3%
C3769
 
5.1%
L3172
 
4.3%
v3073
 
4.1%
i3048
 
4.1%
l2890
 
3.9%
h2861
 
3.9%
p2813
 
3.8%
Other values (32)32968
44.5%
Common
ValueCountFrequency (%)
;12476
77.1%
+1098
 
6.8%
/1010
 
6.2%
#897
 
5.5%
252
 
1.6%
-176
 
1.1%
.170
 
1.1%
699
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII90301
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
;12476
 
13.8%
S8165
 
9.0%
a7460
 
8.3%
t3904
 
4.3%
C3769
 
4.2%
L3172
 
3.5%
v3073
 
3.4%
i3048
 
3.4%
l2890
 
3.2%
h2861
 
3.2%
Other values (40)39483
43.7%

LanguageDesireNextYear
Categorical

HIGH CARDINALITY
MISSING

Distinct1607
Distinct (%)70.5%
Missing667
Missing (%)22.6%
Memory size23.1 KiB
Python
 
28
C#
 
28
C#;JavaScript;SQL;TypeScript;HTML;CSS
 
22
Java
 
20
C#;JavaScript;SQL;HTML;CSS
 
19
Other values (1602)
2162 

Length

Max length257
Median length28
Mean length30.23475208
Min length1

Characters and Unicode

Total characters68905
Distinct characters50
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1377 ?
Unique (%)60.4%

Sample

1st rowJavaScript;Python;HTML;CSS
2nd rowGo;Python
3rd rowC#;JavaScript;SQL;TypeScript;HTML;CSS;Bash/Shell
4th rowAssembly;C;C++;Matlab;SQL;Bash/Shell
5th rowC#;Go;Java;JavaScript;Python;SQL;TypeScript;HTML;CSS

Common Values

ValueCountFrequency (%)
Python28
 
1.0%
C#28
 
1.0%
C#;JavaScript;SQL;TypeScript;HTML;CSS22
 
0.7%
Java20
 
0.7%
C#;JavaScript;SQL;HTML;CSS19
 
0.6%
JavaScript;HTML;CSS16
 
0.5%
TypeScript16
 
0.5%
JavaScript;TypeScript;HTML;CSS15
 
0.5%
Swift15
 
0.5%
C++;Python13
 
0.4%
Other values (1597)2087
70.8%
(Missing)667
 
22.6%

Length

2021-06-21T11:44:13.268793image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
c36
 
1.5%
python28
 
1.2%
c#;javascript;sql;typescript;html;css22
 
0.9%
java20
 
0.9%
c#;javascript;sql;html;css19
 
0.8%
typescript16
 
0.7%
javascript;html;css16
 
0.7%
javascript;typescript;html;css15
 
0.6%
swift15
 
0.6%
basic14
 
0.6%
Other values (1609)2132
91.4%

Most occurring characters

ValueCountFrequency (%)
;9190
 
13.3%
S5500
 
8.0%
a5189
 
7.5%
t3826
 
5.6%
i2607
 
3.8%
l2607
 
3.8%
C2445
 
3.5%
p2300
 
3.3%
h2219
 
3.2%
c2171
 
3.2%
Other values (40)30851
44.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter36019
52.3%
Uppercase Letter21271
30.9%
Other Punctuation10656
 
15.5%
Math Symbol792
 
1.1%
Dash Punctuation99
 
0.1%
Space Separator54
 
0.1%
Decimal Number14
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a5189
14.4%
t3826
10.6%
i2607
 
7.2%
l2607
 
7.2%
p2300
 
6.4%
h2219
 
6.2%
c2171
 
6.0%
o2132
 
5.9%
r2028
 
5.6%
v1972
 
5.5%
Other values (12)8968
24.9%
Uppercase Letter
ValueCountFrequency (%)
S5500
25.9%
C2445
11.5%
J1848
 
8.7%
L1848
 
8.7%
P1768
 
8.3%
T1505
 
7.1%
H1448
 
6.8%
M970
 
4.6%
Q871
 
4.1%
B707
 
3.3%
Other values (10)2361
11.1%
Other Punctuation
ValueCountFrequency (%)
;9190
86.2%
#780
 
7.3%
/631
 
5.9%
.55
 
0.5%
Math Symbol
ValueCountFrequency (%)
+792
100.0%
Space Separator
ValueCountFrequency (%)
54
100.0%
Dash Punctuation
ValueCountFrequency (%)
-99
100.0%
Decimal Number
ValueCountFrequency (%)
614
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin57290
83.1%
Common11615
 
16.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
S5500
 
9.6%
a5189
 
9.1%
t3826
 
6.7%
i2607
 
4.6%
l2607
 
4.6%
C2445
 
4.3%
p2300
 
4.0%
h2219
 
3.9%
c2171
 
3.8%
o2132
 
3.7%
Other values (32)26294
45.9%
Common
ValueCountFrequency (%)
;9190
79.1%
+792
 
6.8%
#780
 
6.7%
/631
 
5.4%
-99
 
0.9%
.55
 
0.5%
54
 
0.5%
614
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII68905
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
;9190
 
13.3%
S5500
 
8.0%
a5189
 
7.5%
t3826
 
5.6%
i2607
 
3.8%
l2607
 
3.8%
C2445
 
3.5%
p2300
 
3.3%
h2219
 
3.2%
c2171
 
3.2%
Other values (40)30851
44.8%

DatabaseWorkedWith
Categorical

HIGH CARDINALITY
MISSING

Distinct691
Distinct (%)32.4%
Missing816
Missing (%)27.7%
Memory size23.1 KiB
SQL Server
196 
MySQL
 
155
SQL Server;MySQL
 
91
PostgreSQL
 
77
SQLite
 
45
Other values (686)
1566 

Length

Max length247
Median length21
Mean length28.01502347
Min length5

Characters and Unicode

Total characters59672
Distinct characters47
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique501 ?
Unique (%)23.5%

Sample

1st rowRedis;SQL Server;MySQL;PostgreSQL;Amazon RDS/Aurora;Microsoft Azure (Tables, CosmosDB, SQL, etc)
2nd rowRedis;PostgreSQL;Memcached
3rd rowSQL Server;Microsoft Azure (Tables, CosmosDB, SQL, etc)
4th rowSQL Server;PostgreSQL;Oracle;IBM Db2
5th rowMongoDB

Common Values

ValueCountFrequency (%)
SQL Server196
 
6.7%
MySQL155
 
5.3%
SQL Server;MySQL91
 
3.1%
PostgreSQL77
 
2.6%
SQLite45
 
1.5%
MySQL;PostgreSQL44
 
1.5%
MongoDB;MySQL39
 
1.3%
MySQL;SQLite35
 
1.2%
MongoDB31
 
1.1%
MySQL;MariaDB31
 
1.1%
Other values (681)1386
47.0%
(Missing)816
27.7%

Length

2021-06-21T11:44:13.639066image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sql815
 
18.0%
server223
 
4.9%
tables168
 
3.7%
cosmosdb168
 
3.7%
azure168
 
3.7%
mysql155
 
3.4%
server;mysql123
 
2.7%
mongodb;sql121
 
2.7%
etc120
 
2.7%
cloud95
 
2.1%
Other values (521)2364
52.3%

Most occurring characters

ValueCountFrequency (%)
e5201
 
8.7%
S4533
 
7.6%
r4199
 
7.0%
;3855
 
6.5%
o3474
 
5.8%
Q3452
 
5.8%
L3405
 
5.7%
a2711
 
4.5%
s2682
 
4.5%
2390
 
4.0%
Other values (37)23770
39.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter32746
54.9%
Uppercase Letter19622
32.9%
Other Punctuation4478
 
7.5%
Space Separator2390
 
4.0%
Open Punctuation168
 
0.3%
Close Punctuation168
 
0.3%
Decimal Number100
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e5201
15.9%
r4199
12.8%
o3474
10.6%
a2711
8.3%
s2682
8.2%
t1949
 
6.0%
i1754
 
5.4%
c1544
 
4.7%
g1516
 
4.6%
y1351
 
4.1%
Other values (12)6365
19.4%
Uppercase Letter
ValueCountFrequency (%)
S4533
23.1%
Q3452
17.6%
L3405
17.4%
M2329
11.9%
D1366
 
7.0%
B1212
 
6.2%
P707
 
3.6%
A642
 
3.3%
R573
 
2.9%
C340
 
1.7%
Other values (7)1063
 
5.4%
Other Punctuation
ValueCountFrequency (%)
;3855
86.1%
,504
 
11.3%
/119
 
2.7%
Decimal Number
ValueCountFrequency (%)
456
56.0%
244
44.0%
Space Separator
ValueCountFrequency (%)
2390
100.0%
Open Punctuation
ValueCountFrequency (%)
(168
100.0%
Close Punctuation
ValueCountFrequency (%)
)168
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin52368
87.8%
Common7304
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e5201
 
9.9%
S4533
 
8.7%
r4199
 
8.0%
o3474
 
6.6%
Q3452
 
6.6%
L3405
 
6.5%
a2711
 
5.2%
s2682
 
5.1%
M2329
 
4.4%
t1949
 
3.7%
Other values (29)18433
35.2%
Common
ValueCountFrequency (%)
;3855
52.8%
2390
32.7%
,504
 
6.9%
(168
 
2.3%
)168
 
2.3%
/119
 
1.6%
456
 
0.8%
244
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII59672
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e5201
 
8.7%
S4533
 
7.6%
r4199
 
7.0%
;3855
 
6.5%
o3474
 
5.8%
Q3452
 
5.8%
L3405
 
5.7%
a2711
 
4.5%
s2682
 
4.5%
2390
 
4.0%
Other values (37)23770
39.8%

DatabaseDesireNextYear
Categorical

HIGH CARDINALITY
MISSING

Distinct819
Distinct (%)44.7%
Missing1115
Missing (%)37.8%
Memory size23.1 KiB
SQL Server
 
89
PostgreSQL
 
78
MongoDB
 
74
MySQL
 
60
SQL Server;Microsoft Azure (Tables, CosmosDB, SQL, etc)
 
31
Other values (814)
1499 

Length

Max length254
Median length26
Mean length35.24904424
Min length5

Characters and Unicode

Total characters64541
Distinct characters47
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique632 ?
Unique (%)34.5%

Sample

1st rowRedis;SQL Server;MySQL;PostgreSQL;Amazon RDS/Aurora;Microsoft Azure (Tables, CosmosDB, SQL, etc)
2nd rowPostgreSQL
3rd rowSQL Server;Microsoft Azure (Tables, CosmosDB, SQL, etc)
4th rowPostgreSQL;Oracle;IBM Db2
5th rowPostgreSQL

Common Values

ValueCountFrequency (%)
SQL Server89
 
3.0%
PostgreSQL78
 
2.6%
MongoDB74
 
2.5%
MySQL60
 
2.0%
SQL Server;Microsoft Azure (Tables, CosmosDB, SQL, etc)31
 
1.1%
SQL Server;MySQL29
 
1.0%
SQLite28
 
1.0%
MongoDB;MySQL27
 
0.9%
MySQL;MariaDB21
 
0.7%
MongoDB;Elasticsearch21
 
0.7%
Other values (809)1373
46.6%
(Missing)1115
37.8%

Length

2021-06-21T11:44:14.449925image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sql554
 
11.7%
cosmosdb255
 
5.4%
azure255
 
5.4%
tables255
 
5.4%
cloud190
 
4.0%
etc135
 
2.9%
storage120
 
2.5%
server111
 
2.3%
mongodb;sql103
 
2.2%
postgresql78
 
1.6%
Other values (560)2677
56.6%

Most occurring characters

ValueCountFrequency (%)
e5148
 
8.0%
o4914
 
7.6%
r3831
 
5.9%
;3775
 
5.8%
a3712
 
5.8%
s3587
 
5.6%
S3104
 
4.8%
2902
 
4.5%
Q2381
 
3.7%
L2244
 
3.5%
Other values (37)28943
44.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter38945
60.3%
Uppercase Letter17343
26.9%
Other Punctuation4690
 
7.3%
Space Separator2902
 
4.5%
Open Punctuation255
 
0.4%
Close Punctuation255
 
0.4%
Decimal Number151
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e5148
13.2%
o4914
12.6%
r3831
9.8%
a3712
9.5%
s3587
9.2%
t2152
 
5.5%
c2023
 
5.2%
i2005
 
5.1%
g1924
 
4.9%
n1498
 
3.8%
Other values (12)8151
20.9%
Uppercase Letter
ValueCountFrequency (%)
S3104
17.9%
Q2381
13.7%
L2244
12.9%
M1915
11.0%
D1718
9.9%
B1577
9.1%
A976
 
5.6%
R694
 
4.0%
C635
 
3.7%
P590
 
3.4%
Other values (7)1509
8.7%
Other Punctuation
ValueCountFrequency (%)
;3775
80.5%
,765
 
16.3%
/150
 
3.2%
Decimal Number
ValueCountFrequency (%)
4132
87.4%
219
 
12.6%
Space Separator
ValueCountFrequency (%)
2902
100.0%
Open Punctuation
ValueCountFrequency (%)
(255
100.0%
Close Punctuation
ValueCountFrequency (%)
)255
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin56288
87.2%
Common8253
 
12.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e5148
 
9.1%
o4914
 
8.7%
r3831
 
6.8%
a3712
 
6.6%
s3587
 
6.4%
S3104
 
5.5%
Q2381
 
4.2%
L2244
 
4.0%
t2152
 
3.8%
c2023
 
3.6%
Other values (29)23192
41.2%
Common
ValueCountFrequency (%)
;3775
45.7%
2902
35.2%
,765
 
9.3%
(255
 
3.1%
)255
 
3.1%
/150
 
1.8%
4132
 
1.6%
219
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII64541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e5148
 
8.0%
o4914
 
7.6%
r3831
 
5.9%
;3775
 
5.8%
a3712
 
5.8%
s3587
 
5.6%
S3104
 
4.8%
2902
 
4.5%
Q2381
 
3.7%
L2244
 
3.5%
Other values (37)28943
44.8%

PlatformWorkedWith
Categorical

HIGH CARDINALITY
MISSING

Distinct764
Distinct (%)36.9%
Missing876
Missing (%)29.7%
Memory size23.1 KiB
Windows Desktop or Server
164 
Linux
 
141
Linux;Windows Desktop or Server
 
84
AWS
 
62
Android
 
53
Other values (759)
1566 

Length

Max length197
Median length25
Mean length28.90048309
Min length3

Characters and Unicode

Total characters59824
Distinct characters48
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique563 ?
Unique (%)27.2%

Sample

1st rowAWS;Azure;Linux;Firebase
2nd rowLinux
3rd rowAzure
4th rowArduino;Windows Desktop or Server
5th rowLinux

Common Values

ValueCountFrequency (%)
Windows Desktop or Server164
 
5.6%
Linux141
 
4.8%
Linux;Windows Desktop or Server84
 
2.9%
AWS62
 
2.1%
Android53
 
1.8%
WordPress41
 
1.4%
AWS;Linux37
 
1.3%
Linux;Mac OS35
 
1.2%
Azure30
 
1.0%
Android;Firebase26
 
0.9%
Other values (754)1397
47.4%
(Missing)876
29.7%

Length

2021-06-21T11:44:14.840568image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
or791
 
13.6%
desktop725
 
12.5%
server564
 
9.7%
cloud201
 
3.5%
windows180
 
3.1%
platform/app168
 
2.9%
linux141
 
2.4%
os134
 
2.3%
pi;windows108
 
1.9%
pi101
 
1.7%
Other values (617)2689
46.3%

Most occurring characters

ValueCountFrequency (%)
r5560
 
9.3%
e4853
 
8.1%
o4716
 
7.9%
3732
 
6.2%
;3722
 
6.2%
i3670
 
6.1%
n3113
 
5.2%
s3082
 
5.2%
d2624
 
4.4%
S2207
 
3.7%
Other values (38)22545
37.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter40785
68.2%
Uppercase Letter11229
 
18.8%
Other Punctuation3890
 
6.5%
Space Separator3732
 
6.2%
Decimal Number188
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r5560
13.6%
e4853
11.9%
o4716
11.6%
i3670
9.0%
n3113
 
7.6%
s3082
 
7.6%
d2624
 
6.4%
u1897
 
4.7%
p1557
 
3.8%
a1481
 
3.6%
Other values (14)8232
20.2%
Uppercase Letter
ValueCountFrequency (%)
S2207
19.7%
A1798
16.0%
W1726
15.4%
L982
8.7%
P968
8.6%
D802
 
7.1%
O691
 
6.2%
M422
 
3.8%
F295
 
2.6%
R287
 
2.6%
Other values (8)1051
9.4%
Decimal Number
ValueCountFrequency (%)
694
50.0%
847
25.0%
247
25.0%
Other Punctuation
ValueCountFrequency (%)
;3722
95.7%
/168
 
4.3%
Space Separator
ValueCountFrequency (%)
3732
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin52014
86.9%
Common7810
 
13.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
r5560
 
10.7%
e4853
 
9.3%
o4716
 
9.1%
i3670
 
7.1%
n3113
 
6.0%
s3082
 
5.9%
d2624
 
5.0%
S2207
 
4.2%
u1897
 
3.6%
A1798
 
3.5%
Other values (32)18494
35.6%
Common
ValueCountFrequency (%)
3732
47.8%
;3722
47.7%
/168
 
2.2%
694
 
1.2%
847
 
0.6%
247
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII59824
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r5560
 
9.3%
e4853
 
8.1%
o4716
 
7.9%
3732
 
6.2%
;3722
 
6.2%
i3670
 
6.1%
n3113
 
5.2%
s3082
 
5.2%
d2624
 
4.4%
S2207
 
3.7%
Other values (38)22545
37.7%

PlatformDesireNextYear
Categorical

HIGH CARDINALITY
MISSING

Distinct938
Distinct (%)49.1%
Missing1037
Missing (%)35.2%
Memory size23.1 KiB
Linux
 
109
Windows Desktop or Server
 
56
Linux;Windows Desktop or Server
 
50
Android
 
45
AWS
 
45
Other values (933)
1604 

Length

Max length302
Median length29
Mean length34.64798324
Min length3

Characters and Unicode

Total characters66143
Distinct characters48
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique739 ?
Unique (%)38.7%

Sample

1st rowAWS;Azure;Linux;Firebase
2nd rowLinux
3rd rowAzure
4th rowArduino;Windows Desktop or Server
5th rowLinux

Common Values

ValueCountFrequency (%)
Linux109
 
3.7%
Windows Desktop or Server56
 
1.9%
Linux;Windows Desktop or Server50
 
1.7%
Android45
 
1.5%
AWS45
 
1.5%
AWS;Linux43
 
1.5%
Firebase30
 
1.0%
Azure23
 
0.8%
Azure;Windows Desktop or Server23
 
0.8%
Linux;Raspberry Pi21
 
0.7%
Other values (928)1464
49.7%
(Missing)1037
35.2%

Length

2021-06-21T11:44:15.230997image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
or625
 
10.5%
desktop470
 
7.9%
server365
 
6.1%
cloud321
 
5.4%
platform/app267
 
4.5%
pi226
 
3.8%
amazon171
 
2.9%
apple134
 
2.2%
os;raspberry112
 
1.9%
os110
 
1.8%
Other values (674)3170
53.1%

Most occurring characters

ValueCountFrequency (%)
r5497
 
8.3%
e5227
 
7.9%
o5118
 
7.7%
;4502
 
6.8%
4062
 
6.1%
i4004
 
6.1%
n3376
 
5.1%
s2812
 
4.3%
d2579
 
3.9%
A2460
 
3.7%
Other values (38)26506
40.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter44571
67.4%
Uppercase Letter12509
 
18.9%
Other Punctuation4769
 
7.2%
Space Separator4062
 
6.1%
Decimal Number232
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r5497
12.3%
e5227
11.7%
o5118
11.5%
i4004
9.0%
n3376
 
7.6%
s2812
 
6.3%
d2579
 
5.8%
a2064
 
4.6%
u1971
 
4.4%
p1940
 
4.4%
Other values (14)9983
22.4%
Uppercase Letter
ValueCountFrequency (%)
A2460
19.7%
S2209
17.7%
W1431
11.4%
P1068
8.5%
L868
 
6.9%
O753
 
6.0%
D510
 
4.1%
G498
 
4.0%
E496
 
4.0%
R492
 
3.9%
Other values (8)1724
13.8%
Decimal Number
ValueCountFrequency (%)
6116
50.0%
858
25.0%
258
25.0%
Other Punctuation
ValueCountFrequency (%)
;4502
94.4%
/267
 
5.6%
Space Separator
ValueCountFrequency (%)
4062
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin57080
86.3%
Common9063
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
r5497
 
9.6%
e5227
 
9.2%
o5118
 
9.0%
i4004
 
7.0%
n3376
 
5.9%
s2812
 
4.9%
d2579
 
4.5%
A2460
 
4.3%
S2209
 
3.9%
a2064
 
3.6%
Other values (32)21734
38.1%
Common
ValueCountFrequency (%)
;4502
49.7%
4062
44.8%
/267
 
2.9%
6116
 
1.3%
858
 
0.6%
258
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII66143
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r5497
 
8.3%
e5227
 
7.9%
o5118
 
7.7%
;4502
 
6.8%
4062
 
6.1%
i4004
 
6.1%
n3376
 
5.1%
s2812
 
4.3%
d2579
 
3.9%
A2460
 
3.7%
Other values (38)26506
40.1%

FrameworkWorkedWith
Categorical

HIGH CARDINALITY
MISSING

Distinct216
Distinct (%)13.2%
Missing1313
Missing (%)44.6%
Memory size23.1 KiB
.NET Core
143 
Spring
113 
Node.js
110 
Node.js;React
 
99
Angular
 
93
Other values (211)
1075 

Length

Max length72
Median length14
Mean length15.32210655
Min length5

Characters and Unicode

Total characters25021
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique116 ?
Unique (%)7.1%

Sample

1st rowDjango;React
2nd rowDjango
3rd rowAngular;Node.js
4th rowNode.js;React
5th rowAngular;Node.js

Common Values

ValueCountFrequency (%)
.NET Core143
 
4.9%
Spring113
 
3.8%
Node.js110
 
3.7%
Node.js;React99
 
3.4%
Angular93
 
3.2%
Angular;Node.js92
 
3.1%
React61
 
2.1%
Django52
 
1.8%
Angular;Node.js;React48
 
1.6%
Angular;.NET Core47
 
1.6%
Other values (206)775
26.3%
(Missing)1313
44.6%

Length

2021-06-21T11:44:15.640304image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
net289
 
13.8%
core190
 
9.1%
angular;.net174
 
8.3%
spring113
 
5.4%
node.js110
 
5.2%
node.js;react99
 
4.7%
angular93
 
4.4%
angular;node.js92
 
4.4%
core;node.js71
 
3.4%
react61
 
2.9%
Other values (190)804
38.4%

Most occurring characters

ValueCountFrequency (%)
o2125
 
8.5%
r1918
 
7.7%
e1791
 
7.2%
a1779
 
7.1%
;1715
 
6.9%
n1370
 
5.5%
N1221
 
4.9%
.1221
 
4.9%
g1132
 
4.5%
d957
 
3.8%
Other values (27)9792
39.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter16669
66.6%
Uppercase Letter4924
 
19.7%
Other Punctuation2965
 
11.9%
Space Separator463
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o2125
12.7%
r1918
11.5%
e1791
10.7%
a1779
10.7%
n1370
8.2%
g1132
 
6.8%
d957
 
5.7%
j948
 
5.7%
s887
 
5.3%
l772
 
4.6%
Other values (11)2990
17.9%
Uppercase Letter
ValueCountFrequency (%)
N1221
24.8%
T650
13.2%
A643
13.1%
C592
12.0%
E463
 
9.4%
R441
 
9.0%
S387
 
7.9%
D190
 
3.9%
F129
 
2.6%
X109
 
2.2%
Other values (2)99
 
2.0%
Other Punctuation
ValueCountFrequency (%)
;1715
57.8%
.1221
41.2%
/29
 
1.0%
Space Separator
ValueCountFrequency (%)
463
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin21593
86.3%
Common3428
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o2125
 
9.8%
r1918
 
8.9%
e1791
 
8.3%
a1779
 
8.2%
n1370
 
6.3%
N1221
 
5.7%
g1132
 
5.2%
d957
 
4.4%
j948
 
4.4%
s887
 
4.1%
Other values (23)7465
34.6%
Common
ValueCountFrequency (%)
;1715
50.0%
.1221
35.6%
463
 
13.5%
/29
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII25021
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o2125
 
8.5%
r1918
 
7.7%
e1791
 
7.2%
a1779
 
7.1%
;1715
 
6.9%
n1370
 
5.5%
N1221
 
4.9%
.1221
 
4.9%
g1132
 
4.5%
d957
 
3.8%
Other values (27)9792
39.1%

FrameworkDesireNextYear
Categorical

HIGH CARDINALITY
MISSING

Distinct363
Distinct (%)21.0%
Missing1215
Missing (%)41.2%
Memory size23.1 KiB
Node.js;React
 
113
.NET Core
 
97
Node.js
 
80
TensorFlow
 
70
React
 
68
Other values (358)
1303 

Length

Max length99
Median length17
Mean length19.96533795
Min length5

Characters and Unicode

Total characters34560
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique204 ?
Unique (%)11.8%

Sample

1st rowDjango;React
2nd rowReact
3rd rowAngular;.NET Core;React
4th rowNode.js
5th rowReact;TensorFlow

Common Values

ValueCountFrequency (%)
Node.js;React113
 
3.8%
.NET Core97
 
3.3%
Node.js80
 
2.7%
TensorFlow70
 
2.4%
React68
 
2.3%
Angular;Node.js;React63
 
2.1%
Angular;Node.js49
 
1.7%
Spring44
 
1.5%
Django41
 
1.4%
Angular35
 
1.2%
Other values (353)1071
36.4%
(Missing)1215
41.2%

Length

2021-06-21T11:44:16.037724image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
net280
 
12.5%
angular;.net228
 
10.2%
core125
 
5.6%
node.js;react113
 
5.0%
node.js80
 
3.6%
tensorflow70
 
3.1%
react68
 
3.0%
angular;node.js;react63
 
2.8%
core;node.js61
 
2.7%
angular;node.js49
 
2.2%
Other values (331)1102
49.2%

Most occurring characters

ValueCountFrequency (%)
o3376
 
9.8%
;2747
 
7.9%
e2561
 
7.4%
r2524
 
7.3%
a2510
 
7.3%
n1755
 
5.1%
.1363
 
3.9%
N1363
 
3.9%
s1303
 
3.8%
T1178
 
3.4%
Other values (27)13880
40.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter23159
67.0%
Uppercase Letter6672
 
19.3%
Other Punctuation4221
 
12.2%
Space Separator508
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o3376
14.6%
e2561
11.1%
r2524
10.9%
a2510
10.8%
n1755
 
7.6%
s1303
 
5.6%
d1176
 
5.1%
g1110
 
4.8%
j1108
 
4.8%
l1062
 
4.6%
Other values (11)4674
20.2%
Uppercase Letter
ValueCountFrequency (%)
N1363
20.4%
T1178
17.7%
R750
11.2%
C622
9.3%
A614
9.2%
E508
 
7.6%
F448
 
6.7%
S421
 
6.3%
D253
 
3.8%
H207
 
3.1%
Other values (2)308
 
4.6%
Other Punctuation
ValueCountFrequency (%)
;2747
65.1%
.1363
32.3%
/111
 
2.6%
Space Separator
ValueCountFrequency (%)
508
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin29831
86.3%
Common4729
 
13.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
o3376
 
11.3%
e2561
 
8.6%
r2524
 
8.5%
a2510
 
8.4%
n1755
 
5.9%
N1363
 
4.6%
s1303
 
4.4%
T1178
 
3.9%
d1176
 
3.9%
g1110
 
3.7%
Other values (23)10975
36.8%
Common
ValueCountFrequency (%)
;2747
58.1%
.1363
28.8%
508
 
10.7%
/111
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII34560
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o3376
 
9.8%
;2747
 
7.9%
e2561
 
7.4%
r2524
 
7.3%
a2510
 
7.3%
n1755
 
5.1%
.1363
 
3.9%
N1363
 
3.9%
s1303
 
3.8%
T1178
 
3.4%
Other values (27)13880
40.2%

IDE
Categorical

HIGH CARDINALITY
MISSING

Distinct839
Distinct (%)35.6%
Missing586
Missing (%)19.9%
Memory size23.1 KiB
Visual Studio;Visual Studio Code
 
83
Notepad++;Visual Studio;Visual Studio Code
 
82
Notepad++;Visual Studio
 
75
Visual Studio
 
66
Visual Studio Code
 
64
Other values (834)
1990 

Length

Max length130
Median length28
Mean length30.99533898
Min length3

Characters and Unicode

Total characters73149
Distinct characters41
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique558 ?
Unique (%)23.6%

Sample

1st rowKomodo;Vim;Visual Studio Code
2nd rowIPython / Jupyter;Sublime Text;Vim
3rd rowVisual Studio;Visual Studio Code
4th rowNotepad++;Visual Studio;Visual Studio Code
5th rowIntelliJ;PyCharm;Visual Studio Code

Common Values

ValueCountFrequency (%)
Visual Studio;Visual Studio Code83
 
2.8%
Notepad++;Visual Studio;Visual Studio Code82
 
2.8%
Notepad++;Visual Studio75
 
2.5%
Visual Studio66
 
2.2%
Visual Studio Code64
 
2.2%
Vim60
 
2.0%
Sublime Text46
 
1.6%
Atom31
 
1.1%
Sublime Text;Visual Studio Code28
 
1.0%
IntelliJ;Vim25
 
0.8%
Other values (829)1800
61.1%
(Missing)586
 
19.9%

Length

2021-06-21T11:44:16.417541image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
studio1258
19.8%
code782
 
12.3%
studio;visual452
 
7.1%
android409
 
6.4%
text;visual244
 
3.8%
visual228
 
3.6%
text220
 
3.5%
notepad++;visual170
 
2.7%
161
 
2.5%
sublime159
 
2.5%
Other values (545)2273
35.8%

Most occurring characters

ValueCountFrequency (%)
i6624
 
9.1%
t5384
 
7.4%
o5302
 
7.2%
d4941
 
6.8%
e4830
 
6.6%
u4773
 
6.5%
;4501
 
6.2%
3996
 
5.5%
l3943
 
5.4%
S3065
 
4.2%
Other values (31)25790
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter50337
68.8%
Uppercase Letter12554
 
17.2%
Other Punctuation4662
 
6.4%
Space Separator3996
 
5.5%
Math Symbol1600
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i6624
13.2%
t5384
10.7%
o5302
10.5%
d4941
9.8%
e4830
9.6%
u4773
9.5%
l3943
7.8%
a3045
6.0%
s2347
 
4.7%
m2260
 
4.5%
Other values (9)6888
13.7%
Uppercase Letter
ValueCountFrequency (%)
S3065
24.4%
V2336
18.6%
C1131
 
9.0%
N969
 
7.7%
A817
 
6.5%
P794
 
6.3%
I740
 
5.9%
J740
 
5.9%
T710
 
5.7%
E473
 
3.8%
Other values (8)779
 
6.2%
Other Punctuation
ValueCountFrequency (%)
;4501
96.5%
/161
 
3.5%
Space Separator
ValueCountFrequency (%)
3996
100.0%
Math Symbol
ValueCountFrequency (%)
+1600
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin62891
86.0%
Common10258
 
14.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i6624
 
10.5%
t5384
 
8.6%
o5302
 
8.4%
d4941
 
7.9%
e4830
 
7.7%
u4773
 
7.6%
l3943
 
6.3%
S3065
 
4.9%
a3045
 
4.8%
s2347
 
3.7%
Other values (27)18637
29.6%
Common
ValueCountFrequency (%)
;4501
43.9%
3996
39.0%
+1600
 
15.6%
/161
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII73149
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i6624
 
9.1%
t5384
 
7.4%
o5302
 
7.2%
d4941
 
6.8%
e4830
 
6.6%
u4773
 
6.5%
;4501
 
6.2%
3996
 
5.5%
l3943
 
5.4%
S3065
 
4.2%
Other values (31)25790
35.3%

OperatingSystem
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct4
Distinct (%)0.2%
Missing569
Missing (%)19.3%
Memory size23.1 KiB
Windows
1151 
MacOS
683 
Linux-based
538 
BSD/Unix
 
5

Length

Max length11
Median length7
Mean length7.332772402
Min length5

Characters and Unicode

Total characters17430
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLinux-based
2nd rowLinux-based
3rd rowWindows
4th rowWindows
5th rowLinux-based

Common Values

ValueCountFrequency (%)
Windows1151
39.1%
MacOS683
23.2%
Linux-based538
18.3%
BSD/Unix5
 
0.2%
(Missing)569
19.3%

Length

2021-06-21T11:44:16.722555image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:16.817389image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
windows1151
48.4%
macos683
28.7%
linux-based538
22.6%
bsd/unix5
 
0.2%

Most occurring characters

ValueCountFrequency (%)
i1694
 
9.7%
n1694
 
9.7%
s1689
 
9.7%
d1689
 
9.7%
a1221
 
7.0%
W1151
 
6.6%
o1151
 
6.6%
w1151
 
6.6%
S688
 
3.9%
M683
 
3.9%
Other values (12)4619
26.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter13129
75.3%
Uppercase Letter3758
 
21.6%
Dash Punctuation538
 
3.1%
Other Punctuation5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i1694
12.9%
n1694
12.9%
s1689
12.9%
d1689
12.9%
a1221
9.3%
o1151
8.8%
w1151
8.8%
c683
5.2%
x543
 
4.1%
u538
 
4.1%
Other values (2)1076
8.2%
Uppercase Letter
ValueCountFrequency (%)
W1151
30.6%
S688
18.3%
M683
18.2%
O683
18.2%
L538
14.3%
B5
 
0.1%
D5
 
0.1%
U5
 
0.1%
Dash Punctuation
ValueCountFrequency (%)
-538
100.0%
Other Punctuation
ValueCountFrequency (%)
/5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin16887
96.9%
Common543
 
3.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
i1694
10.0%
n1694
10.0%
s1689
10.0%
d1689
10.0%
a1221
 
7.2%
W1151
 
6.8%
o1151
 
6.8%
w1151
 
6.8%
S688
 
4.1%
M683
 
4.0%
Other values (10)4076
24.1%
Common
ValueCountFrequency (%)
-538
99.1%
/5
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII17430
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i1694
 
9.7%
n1694
 
9.7%
s1689
 
9.7%
d1689
 
9.7%
a1221
 
7.0%
W1151
 
6.6%
o1151
 
6.6%
w1151
 
6.6%
S688
 
3.9%
M683
 
3.9%
Other values (12)4619
26.5%

Methodology
Categorical

HIGH CARDINALITY
MISSING

Distinct155
Distinct (%)7.8%
Missing955
Missing (%)32.4%
Memory size23.1 KiB
Agile;Scrum
344 
Agile
296 
Agile;Kanban;Scrum
204 
Agile;Kanban;Pair programming;Scrum
 
90
Scrum
 
82
Other values (150)
975 

Length

Max length192
Median length18
Mean length32.89050728
Min length4

Characters and Unicode

Total characters65485
Distinct characters47
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)3.2%

Sample

1st rowAgile;Scrum
2nd rowAgile;Kanban;Scrum
3rd rowEvidence-based software engineering;Formal standard such as ISO 9001 or IEEE 12207 (aka �waterfall� methodologies)
4th rowAgile
5th rowAgile;Scrum

Common Values

ValueCountFrequency (%)
Agile;Scrum344
 
11.7%
Agile296
 
10.0%
Agile;Kanban;Scrum204
 
6.9%
Agile;Kanban;Pair programming;Scrum90
 
3.1%
Scrum82
 
2.8%
Agile;Pair programming;Scrum78
 
2.6%
Agile;Kanban72
 
2.4%
Agile;Pair programming44
 
1.5%
Agile;Formal standard such as ISO 9001 or IEEE 12207 (aka �waterfall� methodologies);Scrum42
 
1.4%
Agile;Extreme programming (XP);Kanban;Pair programming;Scrum35
 
1.2%
Other values (145)704
23.9%
(Missing)955
32.4%

Length

2021-06-21T11:44:17.197664image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
programming444
 
6.8%
programming;scrum403
 
6.2%
agile;scrum344
 
5.3%
agile296
 
4.5%
or293
 
4.5%
9001293
 
4.5%
standard293
 
4.5%
12207293
 
4.5%
iso293
 
4.5%
�waterfall�293
 
4.5%
Other values (83)3290
50.3%

Most occurring characters

ValueCountFrequency (%)
a5630
 
8.6%
r5227
 
8.0%
4544
 
6.9%
g3951
 
6.0%
m3938
 
6.0%
e3831
 
5.9%
i3681
 
5.6%
;3217
 
4.9%
n3168
 
4.8%
l2884
 
4.4%
Other values (37)25414
38.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter45351
69.3%
Uppercase Letter7919
 
12.1%
Space Separator4544
 
6.9%
Other Punctuation3217
 
4.9%
Decimal Number2659
 
4.1%
Other Symbol586
 
0.9%
Open Punctuation568
 
0.9%
Close Punctuation568
 
0.9%
Dash Punctuation73
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a5630
12.4%
r5227
11.5%
g3951
8.7%
m3938
8.7%
e3831
8.4%
i3681
8.1%
n3168
 
7.0%
l2884
 
6.4%
o2506
 
5.5%
c1643
 
3.6%
Other values (12)8892
19.6%
Uppercase Letter
ValueCountFrequency (%)
A1712
21.6%
S1570
19.8%
E1249
15.8%
P854
10.8%
K752
9.5%
I608
 
7.7%
F293
 
3.7%
O293
 
3.7%
X275
 
3.5%
L179
 
2.3%
Other values (4)134
 
1.7%
Decimal Number
ValueCountFrequency (%)
0879
33.1%
2608
22.9%
1586
22.0%
9293
 
11.0%
7293
 
11.0%
Other Punctuation
ValueCountFrequency (%)
;3217
100.0%
Dash Punctuation
ValueCountFrequency (%)
-73
100.0%
Space Separator
ValueCountFrequency (%)
4544
100.0%
Open Punctuation
ValueCountFrequency (%)
(568
100.0%
Other Symbol
ValueCountFrequency (%)
586
100.0%
Close Punctuation
ValueCountFrequency (%)
)568
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin53270
81.3%
Common12215
 
18.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
a5630
 
10.6%
r5227
 
9.8%
g3951
 
7.4%
m3938
 
7.4%
e3831
 
7.2%
i3681
 
6.9%
n3168
 
5.9%
l2884
 
5.4%
o2506
 
4.7%
A1712
 
3.2%
Other values (26)16742
31.4%
Common
ValueCountFrequency (%)
4544
37.2%
;3217
26.3%
0879
 
7.2%
2608
 
5.0%
1586
 
4.8%
586
 
4.8%
(568
 
4.7%
)568
 
4.7%
9293
 
2.4%
7293
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII64899
99.1%
Specials586
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a5630
 
8.7%
r5227
 
8.1%
4544
 
7.0%
g3951
 
6.1%
m3938
 
6.1%
e3831
 
5.9%
i3681
 
5.7%
;3217
 
5.0%
n3168
 
4.9%
l2884
 
4.4%
Other values (36)24828
38.3%
Specials
ValueCountFrequency (%)
586
100.0%

VersionControl
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct49
Distinct (%)2.1%
Missing614
Missing (%)20.8%
Memory size23.1 KiB
Git
1379 
Git;Subversion
223 
Git;Team Foundation Version Control
164 
Subversion
 
80
Team Foundation Version Control
 
69
Other values (44)
417 

Length

Max length108
Median length3
Mean length14.0754717
Min length3

Characters and Unicode

Total characters32824
Distinct characters35
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)0.6%

Sample

1st rowGit
2nd rowGit;Subversion
3rd rowGit
4th rowZip file back-ups
5th rowGit

Common Values

ValueCountFrequency (%)
Git1379
46.8%
Git;Subversion223
 
7.6%
Git;Team Foundation Version Control164
 
5.6%
Subversion80
 
2.7%
Team Foundation Version Control69
 
2.3%
I don't use version control53
 
1.8%
Git;Mercurial49
 
1.7%
Git;Copying and pasting files to network shares45
 
1.5%
Git;Zip file back-ups39
 
1.3%
Git;Copying and pasting files to network shares;Zip file back-ups32
 
1.1%
Other values (39)199
 
6.8%
(Missing)614
20.8%

Length

2021-06-21T11:44:17.589360image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
git1379
28.6%
version370
 
7.7%
control335
 
7.0%
foundation307
 
6.4%
git;subversion223
 
4.6%
git;team176
 
3.7%
network169
 
3.5%
pasting169
 
3.5%
files169
 
3.5%
and169
 
3.5%
Other values (36)1351
28.0%

Most occurring characters

ValueCountFrequency (%)
i4010
12.2%
t3286
 
10.0%
o2698
 
8.2%
n2497
 
7.6%
2485
 
7.6%
G2039
 
6.2%
e1885
 
5.7%
s1662
 
5.1%
r1652
 
5.0%
a1355
 
4.1%
Other values (25)9255
28.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter25106
76.5%
Uppercase Letter4137
 
12.6%
Space Separator2485
 
7.6%
Other Punctuation947
 
2.9%
Dash Punctuation149
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i4010
16.0%
t3286
13.1%
o2698
10.7%
n2497
9.9%
e1885
7.5%
s1662
 
6.6%
r1652
 
6.6%
a1355
 
5.4%
u1008
 
4.0%
l773
 
3.1%
Other values (12)4280
17.0%
Uppercase Letter
ValueCountFrequency (%)
G2039
49.3%
C476
 
11.5%
S404
 
9.8%
T307
 
7.4%
F307
 
7.4%
V307
 
7.4%
Z149
 
3.6%
M85
 
2.1%
I63
 
1.5%
Other Punctuation
ValueCountFrequency (%)
;884
93.3%
'63
 
6.7%
Space Separator
ValueCountFrequency (%)
2485
100.0%
Dash Punctuation
ValueCountFrequency (%)
-149
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin29243
89.1%
Common3581
 
10.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
i4010
13.7%
t3286
11.2%
o2698
 
9.2%
n2497
 
8.5%
G2039
 
7.0%
e1885
 
6.4%
s1662
 
5.7%
r1652
 
5.6%
a1355
 
4.6%
u1008
 
3.4%
Other values (21)7151
24.5%
Common
ValueCountFrequency (%)
2485
69.4%
;884
 
24.7%
-149
 
4.2%
'63
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII32824
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i4010
12.2%
t3286
 
10.0%
o2698
 
8.2%
n2497
 
7.6%
2485
 
7.6%
G2039
 
6.2%
e1885
 
5.7%
s1662
 
5.1%
r1652
 
5.0%
a1355
 
4.1%
Other values (25)9255
28.2%

CheckInCode
Categorical

HIGH CORRELATION
MISSING

Distinct6
Distinct (%)0.3%
Missing627
Missing (%)21.3%
Memory size23.1 KiB
Multiple times per day
1485 
A few times per week
406 
Once a day
212 
Weekly or a few times per month
 
139
Less than once per month
 
51

Length

Max length31
Median length22
Mean length20.94566624
Min length5

Characters and Unicode

Total characters48573
Distinct characters27
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMultiple times per day
2nd rowA few times per week
3rd rowMultiple times per day
4th rowWeekly or a few times per month
5th rowA few times per week

Common Values

ValueCountFrequency (%)
Multiple times per day1485
50.4%
A few times per week406
 
13.8%
Once a day212
 
7.2%
Weekly or a few times per month139
 
4.7%
Less than once per month51
 
1.7%
Never26
 
0.9%
(Missing)627
21.3%

Length

2021-06-21T11:44:17.913473image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:18.011858image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
per2081
21.1%
times2030
20.6%
day1697
17.2%
multiple1485
15.1%
a757
 
7.7%
few545
 
5.5%
week406
 
4.1%
once263
 
2.7%
month190
 
1.9%
weekly139
 
1.4%
Other values (4)267
 
2.7%

Most occurring characters

ValueCountFrequency (%)
e7597
15.6%
7541
15.5%
t3756
 
7.7%
p3566
 
7.3%
i3515
 
7.2%
l3109
 
6.4%
r2246
 
4.6%
m2220
 
4.6%
s2132
 
4.4%
a2099
 
4.3%
Other values (17)10792
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter38713
79.7%
Space Separator7541
 
15.5%
Uppercase Letter2319
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e7597
19.6%
t3756
9.7%
p3566
9.2%
i3515
9.1%
l3109
8.0%
r2246
 
5.8%
m2220
 
5.7%
s2132
 
5.5%
a2099
 
5.4%
y1836
 
4.7%
Other values (10)6637
17.1%
Uppercase Letter
ValueCountFrequency (%)
M1485
64.0%
A406
 
17.5%
O212
 
9.1%
W139
 
6.0%
L51
 
2.2%
N26
 
1.1%
Space Separator
ValueCountFrequency (%)
7541
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin41032
84.5%
Common7541
 
15.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
e7597
18.5%
t3756
9.2%
p3566
 
8.7%
i3515
 
8.6%
l3109
 
7.6%
r2246
 
5.5%
m2220
 
5.4%
s2132
 
5.2%
a2099
 
5.1%
y1836
 
4.5%
Other values (16)8956
21.8%
Common
ValueCountFrequency (%)
7541
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII48573
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e7597
15.6%
7541
15.5%
t3756
 
7.7%
p3566
 
7.3%
i3515
 
7.2%
l3109
 
6.4%
r2246
 
4.6%
m2220
 
4.6%
s2132
 
4.4%
a2099
 
4.3%
Other values (17)10792
22.2%

AIDangerous
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)0.2%
Missing946
Missing (%)32.1%
Memory size23.1 KiB
Algorithms making important decisions
598 
Artificial intelligence surpassing human intelligence ("the singularity")
528 
Evolving definitions of "fairness" in algorithmic versus human decisions
482 
Increasing automation of jobs
392 

Length

Max length73
Median length72
Mean length53.371
Min length29

Characters and Unicode

Total characters106742
Distinct characters29
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowArtificial intelligence surpassing human intelligence ("the singularity")
2nd rowIncreasing automation of jobs
3rd rowArtificial intelligence surpassing human intelligence ("the singularity")
4th rowAlgorithms making important decisions
5th rowIncreasing automation of jobs

Common Values

ValueCountFrequency (%)
Algorithms making important decisions598
20.3%
Artificial intelligence surpassing human intelligence ("the singularity")528
17.9%
Evolving definitions of "fairness" in algorithmic versus human decisions482
16.4%
Increasing automation of jobs392
13.3%
(Missing)946
32.1%

Length

2021-06-21T11:44:18.312082image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:18.404505image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
decisions1080
 
9.0%
intelligence1056
 
8.8%
human1010
 
8.4%
of874
 
7.3%
algorithms598
 
5.0%
making598
 
5.0%
important598
 
5.0%
surpassing528
 
4.4%
artificial528
 
4.4%
singularity528
 
4.4%
Other values (10)4596
38.3%

Most occurring characters

ValueCountFrequency (%)
i13874
13.0%
n10040
 
9.4%
9994
 
9.4%
s8064
 
7.6%
e6614
 
6.2%
t6182
 
5.8%
a5930
 
5.6%
o5772
 
5.4%
l4730
 
4.4%
g4664
 
4.4%
Other values (19)30878
28.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter91672
85.9%
Space Separator9994
 
9.4%
Other Punctuation2020
 
1.9%
Uppercase Letter2000
 
1.9%
Open Punctuation528
 
0.5%
Close Punctuation528
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i13874
15.1%
n10040
11.0%
s8064
 
8.8%
e6614
 
7.2%
t6182
 
6.7%
a5930
 
6.5%
o5772
 
6.3%
l4730
 
5.2%
g4664
 
5.1%
r4618
 
5.0%
Other values (12)21184
23.1%
Uppercase Letter
ValueCountFrequency (%)
A1126
56.3%
E482
24.1%
I392
 
19.6%
Space Separator
ValueCountFrequency (%)
9994
100.0%
Open Punctuation
ValueCountFrequency (%)
(528
100.0%
Other Punctuation
ValueCountFrequency (%)
"2020
100.0%
Close Punctuation
ValueCountFrequency (%)
)528
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin93672
87.8%
Common13070
 
12.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
i13874
14.8%
n10040
10.7%
s8064
 
8.6%
e6614
 
7.1%
t6182
 
6.6%
a5930
 
6.3%
o5772
 
6.2%
l4730
 
5.0%
g4664
 
5.0%
r4618
 
4.9%
Other values (15)23184
24.8%
Common
ValueCountFrequency (%)
9994
76.5%
"2020
 
15.5%
(528
 
4.0%
)528
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII106742
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i13874
13.0%
n10040
 
9.4%
9994
 
9.4%
s8064
 
7.6%
e6614
 
6.2%
t6182
 
5.8%
a5930
 
5.6%
o5772
 
5.4%
l4730
 
4.4%
g4664
 
4.4%
Other values (19)30878
28.9%

AIInteresting
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)0.2%
Missing870
Missing (%)29.5%
Memory size23.1 KiB
Increasing automation of jobs
871 
Artificial intelligence surpassing human intelligence ("the singularity")
478 
Algorithms making important decisions
469 
Evolving definitions of "fairness" in algorithmic versus human decisions
258 

Length

Max length73
Median length37
Mean length46.2822736
Min length29

Characters and Unicode

Total characters96082
Distinct characters29
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAlgorithms making important decisions
2nd rowIncreasing automation of jobs
3rd rowArtificial intelligence surpassing human intelligence ("the singularity")
4th rowAlgorithms making important decisions
5th rowAlgorithms making important decisions

Common Values

ValueCountFrequency (%)
Increasing automation of jobs871
29.6%
Artificial intelligence surpassing human intelligence ("the singularity")478
16.2%
Algorithms making important decisions469
15.9%
Evolving definitions of "fairness" in algorithmic versus human decisions258
 
8.8%
(Missing)870
29.5%

Length

2021-06-21T11:44:18.738042image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:18.839335image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
of1129
 
10.2%
intelligence956
 
8.7%
increasing871
 
7.9%
automation871
 
7.9%
jobs871
 
7.9%
human736
 
6.7%
decisions727
 
6.6%
the478
 
4.3%
singularity478
 
4.3%
surpassing478
 
4.3%
Other values (10)3433
31.1%

Most occurring characters

ValueCountFrequency (%)
i11447
11.9%
n9172
 
9.5%
8952
 
9.3%
s6867
 
7.1%
a6237
 
6.5%
o6181
 
6.4%
t6055
 
6.3%
e5718
 
6.0%
g4237
 
4.4%
r4017
 
4.2%
Other values (19)27199
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter82626
86.0%
Space Separator8952
 
9.3%
Uppercase Letter2076
 
2.2%
Other Punctuation1472
 
1.5%
Open Punctuation478
 
0.5%
Close Punctuation478
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i11447
13.9%
n9172
11.1%
s6867
 
8.3%
a6237
 
7.5%
o6181
 
7.5%
t6055
 
7.3%
e5718
 
6.9%
g4237
 
5.1%
r4017
 
4.9%
l3853
 
4.7%
Other values (12)18842
22.8%
Uppercase Letter
ValueCountFrequency (%)
A947
45.6%
I871
42.0%
E258
 
12.4%
Space Separator
ValueCountFrequency (%)
8952
100.0%
Open Punctuation
ValueCountFrequency (%)
(478
100.0%
Other Punctuation
ValueCountFrequency (%)
"1472
100.0%
Close Punctuation
ValueCountFrequency (%)
)478
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin84702
88.2%
Common11380
 
11.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
i11447
13.5%
n9172
10.8%
s6867
 
8.1%
a6237
 
7.4%
o6181
 
7.3%
t6055
 
7.1%
e5718
 
6.8%
g4237
 
5.0%
r4017
 
4.7%
l3853
 
4.5%
Other values (15)20918
24.7%
Common
ValueCountFrequency (%)
8952
78.7%
"1472
 
12.9%
(478
 
4.2%
)478
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII96082
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i11447
11.9%
n9172
 
9.5%
8952
 
9.3%
s6867
 
7.1%
a6237
 
6.5%
o6181
 
6.4%
t6055
 
6.3%
e5718
 
6.0%
g4237
 
4.4%
r4017
 
4.2%
Other values (19)27199
28.3%

AIResponsible
Categorical

HIGH CORRELATION
MISSING

Distinct4
Distinct (%)0.2%
Missing876
Missing (%)29.7%
Memory size23.1 KiB
The developers or the people creating the AI
992 
A governmental or other regulatory body
597 
Prominent industry leaders
316 
Nobody
165 

Length

Max length44
Median length39
Mean length36.78115942
Min length6

Characters and Unicode

Total characters76137
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowThe developers or the people creating the AI
2nd rowThe developers or the people creating the AI
3rd rowA governmental or other regulatory body
4th rowThe developers or the people creating the AI
5th rowA governmental or other regulatory body

Common Values

ValueCountFrequency (%)
The developers or the people creating the AI992
33.7%
A governmental or other regulatory body597
20.3%
Prominent industry leaders316
 
10.7%
Nobody165
 
5.6%
(Missing)876
29.7%

Length

2021-06-21T11:44:19.156192image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:19.276761image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
the2976
23.6%
or1589
12.6%
developers992
 
7.9%
creating992
 
7.9%
ai992
 
7.9%
people992
 
7.9%
governmental597
 
4.7%
a597
 
4.7%
body597
 
4.7%
other597
 
4.7%
Other values (5)1710
13.5%

Most occurring characters

ValueCountFrequency (%)
e12264
16.1%
10561
13.9%
r6909
 
9.1%
o6607
 
8.7%
t5399
 
7.1%
h3573
 
4.7%
l3494
 
4.6%
n3134
 
4.1%
p2976
 
3.9%
a2502
 
3.3%
Other values (15)18718
24.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter61522
80.8%
Space Separator10561
 
13.9%
Uppercase Letter4054
 
5.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e12264
19.9%
r6909
11.2%
o6607
10.7%
t5399
8.8%
h3573
 
5.8%
l3494
 
5.7%
n3134
 
5.1%
p2976
 
4.8%
a2502
 
4.1%
d2386
 
3.9%
Other values (9)12278
20.0%
Uppercase Letter
ValueCountFrequency (%)
A1589
39.2%
T992
24.5%
I992
24.5%
P316
 
7.8%
N165
 
4.1%
Space Separator
ValueCountFrequency (%)
10561
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin65576
86.1%
Common10561
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e12264
18.7%
r6909
10.5%
o6607
10.1%
t5399
 
8.2%
h3573
 
5.4%
l3494
 
5.3%
n3134
 
4.8%
p2976
 
4.5%
a2502
 
3.8%
d2386
 
3.6%
Other values (14)16332
24.9%
Common
ValueCountFrequency (%)
10561
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII76137
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e12264
16.1%
10561
13.9%
r6909
 
9.1%
o6607
 
8.7%
t5399
 
7.1%
h3573
 
4.7%
l3494
 
4.6%
n3134
 
4.1%
p2976
 
3.9%
a2502
 
3.3%
Other values (15)18718
24.6%

AIFuture
Categorical

HIGH CORRELATION
MISSING

Distinct3
Distinct (%)0.1%
Missing750
Missing (%)25.5%
Memory size23.1 KiB
I'm excited about the possibilities more than worried about the dangers.
1601 
I'm worried about the dangers more than I'm excited about the possibilities.
402 
I don't care about it, or I haven't thought about it.
193 

Length

Max length76
Median length72
Mean length71.06238616
Min length53

Characters and Unicode

Total characters156053
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowI'm excited about the possibilities more than worried about the dangers.
2nd rowI'm excited about the possibilities more than worried about the dangers.
3rd rowI don't care about it, or I haven't thought about it.
4th rowI'm excited about the possibilities more than worried about the dangers.
5th rowI'm excited about the possibilities more than worried about the dangers.

Common Values

ValueCountFrequency (%)
I'm excited about the possibilities more than worried about the dangers.1601
54.3%
I'm worried about the dangers more than I'm excited about the possibilities.402
 
13.6%
I don't care about it, or I haven't thought about it.193
 
6.6%
(Missing)750
25.5%

Length

2021-06-21T11:44:19.591705image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:19.693976image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
about4392
17.9%
the4006
16.3%
i'm2405
9.8%
more2003
8.2%
worried2003
8.2%
excited2003
8.2%
than2003
8.2%
possibilities2003
8.2%
dangers2003
8.2%
i386
 
1.6%
Other values (6)1351
 
5.5%

Most occurring characters

ValueCountFrequency (%)
22362
14.3%
e16410
10.5%
t15565
 
10.0%
i12404
 
7.9%
o10980
 
7.0%
a8784
 
5.6%
r8398
 
5.4%
s8012
 
5.1%
h6588
 
4.2%
b6395
 
4.1%
Other values (15)40155
25.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter125720
80.6%
Space Separator22362
 
14.3%
Other Punctuation5180
 
3.3%
Uppercase Letter2791
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e16410
13.1%
t15565
12.4%
i12404
9.9%
o10980
8.7%
a8784
 
7.0%
r8398
 
6.7%
s8012
 
6.4%
h6588
 
5.2%
b6395
 
5.1%
d6202
 
4.9%
Other values (10)25982
20.7%
Other Punctuation
ValueCountFrequency (%)
'2791
53.9%
.2196
42.4%
,193
 
3.7%
Uppercase Letter
ValueCountFrequency (%)
I2791
100.0%
Space Separator
ValueCountFrequency (%)
22362
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin128511
82.4%
Common27542
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e16410
12.8%
t15565
12.1%
i12404
9.7%
o10980
 
8.5%
a8784
 
6.8%
r8398
 
6.5%
s8012
 
6.2%
h6588
 
5.1%
b6395
 
5.0%
d6202
 
4.8%
Other values (11)28773
22.4%
Common
ValueCountFrequency (%)
22362
81.2%
'2791
 
10.1%
.2196
 
8.0%
,193
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII156053
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
22362
14.3%
e16410
10.5%
t15565
 
10.0%
i12404
 
7.9%
o10980
 
7.0%
a8784
 
5.6%
r8398
 
5.4%
s8012
 
5.1%
h6588
 
4.2%
b6395
 
4.1%
Other values (15)40155
25.7%

Age
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct6
Distinct (%)0.3%
Missing919
Missing (%)31.2%
Memory size23.1 KiB
25 - 34 years old
1117 
18 - 24 years old
421 
35 - 44 years old
364 
45 - 54 years old
 
93
55 - 64 years old
 
23

Length

Max length18
Median length17
Mean length17.00444006
Min length17

Characters and Unicode

Total characters34468
Distinct characters19
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row25 - 34 years old
2nd row35 - 44 years old
3rd row35 - 44 years old
4th row18 - 24 years old
5th row18 - 24 years old

Common Values

ValueCountFrequency (%)
25 - 34 years old1117
37.9%
18 - 24 years old421
 
14.3%
35 - 44 years old364
 
12.4%
45 - 54 years old93
 
3.2%
55 - 64 years old23
 
0.8%
Under 18 years old9
 
0.3%
(Missing)919
31.2%

Length

2021-06-21T11:44:19.995226image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:20.101336image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
years2027
20.0%
old2027
20.0%
2018
19.9%
251117
11.0%
341117
11.0%
18430
 
4.2%
24421
 
4.2%
44364
 
3.6%
35364
 
3.6%
4593
 
0.9%
Other values (4)148
 
1.5%

Most occurring characters

ValueCountFrequency (%)
8099
23.5%
42475
 
7.2%
e2036
 
5.9%
r2036
 
5.9%
d2036
 
5.9%
y2027
 
5.9%
a2027
 
5.9%
s2027
 
5.9%
o2027
 
5.9%
l2027
 
5.9%
Other values (9)7651
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter16252
47.2%
Space Separator8099
23.5%
Decimal Number8090
23.5%
Dash Punctuation2018
 
5.9%
Uppercase Letter9
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e2036
12.5%
r2036
12.5%
d2036
12.5%
y2027
12.5%
a2027
12.5%
s2027
12.5%
o2027
12.5%
l2027
12.5%
n9
 
0.1%
Decimal Number
ValueCountFrequency (%)
42475
30.6%
51713
21.2%
21538
19.0%
31481
18.3%
1430
 
5.3%
8430
 
5.3%
623
 
0.3%
Space Separator
ValueCountFrequency (%)
8099
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2018
100.0%
Uppercase Letter
ValueCountFrequency (%)
U9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common18207
52.8%
Latin16261
47.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e2036
12.5%
r2036
12.5%
d2036
12.5%
y2027
12.5%
a2027
12.5%
s2027
12.5%
o2027
12.5%
l2027
12.5%
U9
 
0.1%
n9
 
0.1%
Common
ValueCountFrequency (%)
8099
44.5%
42475
 
13.6%
-2018
 
11.1%
51713
 
9.4%
21538
 
8.4%
31481
 
8.1%
1430
 
2.4%
8430
 
2.4%
623
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII34468
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8099
23.5%
42475
 
7.2%
e2036
 
5.9%
r2036
 
5.9%
d2036
 
5.9%
y2027
 
5.9%
a2027
 
5.9%
s2027
 
5.9%
o2027
 
5.9%
l2027
 
5.9%
Other values (9)7651
22.2%

term
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
36 months
2059 
60 months
887 

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters29460
Distinct characters10
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row 36 months
2nd row 36 months
3rd row 60 months
4th row 60 months
5th row 60 months

Common Values

ValueCountFrequency (%)
36 months2059
69.9%
60 months887
30.1%

Length

2021-06-21T11:44:20.409576image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:20.496326image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
months2946
50.0%
362059
34.9%
60887
 
15.1%

Most occurring characters

ValueCountFrequency (%)
5892
20.0%
62946
10.0%
m2946
10.0%
o2946
10.0%
n2946
10.0%
t2946
10.0%
h2946
10.0%
s2946
10.0%
32059
 
7.0%
0887
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter17676
60.0%
Space Separator5892
 
20.0%
Decimal Number5892
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
m2946
16.7%
o2946
16.7%
n2946
16.7%
t2946
16.7%
h2946
16.7%
s2946
16.7%
Decimal Number
ValueCountFrequency (%)
62946
50.0%
32059
34.9%
0887
 
15.1%
Space Separator
ValueCountFrequency (%)
5892
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin17676
60.0%
Common11784
40.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
m2946
16.7%
o2946
16.7%
n2946
16.7%
t2946
16.7%
h2946
16.7%
s2946
16.7%
Common
ValueCountFrequency (%)
5892
50.0%
62946
25.0%
32059
 
17.5%
0887
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII29460
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5892
20.0%
62946
10.0%
m2946
10.0%
o2946
10.0%
n2946
10.0%
t2946
10.0%
h2946
10.0%
s2946
10.0%
32059
 
7.0%
0887
 
3.0%

loan_status
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct6
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
Fully Paid
2154 
Charged Off
456 
Current
319 
Late (31-120 days)
 
14
In Grace Period
 
2

Length

Max length18
Median length10
Mean length9.873727088
Min length7

Characters and Unicode

Total characters29088
Distinct characters32
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowFully Paid
2nd rowFully Paid
3rd rowFully Paid
4th rowCurrent
5th rowFully Paid

Common Values

ValueCountFrequency (%)
Fully Paid2154
73.1%
Charged Off456
 
15.5%
Current319
 
10.8%
Late (31-120 days)14
 
0.5%
In Grace Period2
 
0.1%
Late (16-30 days)1
 
< 0.1%

Length

2021-06-21T11:44:20.754634image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:20.847180image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
fully2154
38.5%
paid2154
38.5%
off456
 
8.2%
charged456
 
8.2%
current319
 
5.7%
late15
 
0.3%
days15
 
0.3%
31-12014
 
0.3%
in2
 
< 0.1%
period2
 
< 0.1%
Other values (2)3
 
0.1%

Most occurring characters

ValueCountFrequency (%)
l4308
14.8%
2644
9.1%
a2642
9.1%
d2627
9.0%
u2473
8.5%
y2169
7.5%
P2156
7.4%
i2156
7.4%
F2154
7.4%
r1098
 
3.8%
Other values (22)4661
16.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter20765
71.4%
Uppercase Letter5560
 
19.1%
Space Separator2644
 
9.1%
Decimal Number74
 
0.3%
Open Punctuation15
 
0.1%
Dash Punctuation15
 
0.1%
Close Punctuation15
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l4308
20.7%
a2642
12.7%
d2627
12.7%
u2473
11.9%
y2169
10.4%
i2156
10.4%
r1098
 
5.3%
f912
 
4.4%
e794
 
3.8%
h456
 
2.2%
Other values (6)1130
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
P2156
38.8%
F2154
38.7%
C775
 
13.9%
O456
 
8.2%
L15
 
0.3%
I2
 
< 0.1%
G2
 
< 0.1%
Decimal Number
ValueCountFrequency (%)
129
39.2%
315
20.3%
015
20.3%
214
18.9%
61
 
1.4%
Space Separator
ValueCountFrequency (%)
2644
100.0%
Open Punctuation
ValueCountFrequency (%)
(15
100.0%
Dash Punctuation
ValueCountFrequency (%)
-15
100.0%
Close Punctuation
ValueCountFrequency (%)
)15
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin26325
90.5%
Common2763
 
9.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
l4308
16.4%
a2642
10.0%
d2627
10.0%
u2473
9.4%
y2169
8.2%
P2156
8.2%
i2156
8.2%
F2154
8.2%
r1098
 
4.2%
f912
 
3.5%
Other values (13)3630
13.8%
Common
ValueCountFrequency (%)
2644
95.7%
129
 
1.0%
(15
 
0.5%
315
 
0.5%
-15
 
0.5%
015
 
0.5%
)15
 
0.5%
214
 
0.5%
61
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII29088
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l4308
14.8%
2644
9.1%
a2642
9.1%
d2627
9.0%
u2473
8.5%
y2169
7.5%
P2156
7.4%
i2156
7.4%
F2154
7.4%
r1098
 
3.8%
Other values (22)4661
16.0%

pymnt_plan
Boolean

CONSTANT
HIGH CORRELATION
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
False
2946 
ValueCountFrequency (%)
False2946
100.0%
2021-06-21T11:44:20.973617image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

orignal_website_directory
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct2946
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
https://lendingclub.com/browse/loanDetail.action?loan_id=68547583
 
1
https://lendingclub.com/browse/loanDetail.action?loan_id=66615787
 
1
https://lendingclub.com/browse/loanDetail.action?loan_id=68476668
 
1
https://lendingclub.com/browse/loanDetail.action?loan_id=68365168
 
1
https://lendingclub.com/browse/loanDetail.action?loan_id=68414215
 
1
Other values (2941)
2941 

Length

Max length65
Median length65
Mean length64.99864223
Min length63

Characters and Unicode

Total characters191486
Distinct characters35
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2946 ?
Unique (%)100.0%

Sample

1st rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=68407277
2nd rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=68355089
3rd rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=68341763
4th rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=66310712
5th rowhttps://lendingclub.com/browse/loanDetail.action?loan_id=68476807

Common Values

ValueCountFrequency (%)
https://lendingclub.com/browse/loanDetail.action?loan_id=685475831
 
< 0.1%
https://lendingclub.com/browse/loanDetail.action?loan_id=666157871
 
< 0.1%
https://lendingclub.com/browse/loanDetail.action?loan_id=684766681
 
< 0.1%
https://lendingclub.com/browse/loanDetail.action?loan_id=683651681
 
< 0.1%
https://lendingclub.com/browse/loanDetail.action?loan_id=684142151
 
< 0.1%
https://lendingclub.com/browse/loanDetail.action?loan_id=685659211
 
< 0.1%
https://lendingclub.com/browse/loanDetail.action?loan_id=684133341
 
< 0.1%
https://lendingclub.com/browse/loanDetail.action?loan_id=684865981
 
< 0.1%
https://lendingclub.com/browse/loanDetail.action?loan_id=684754011
 
< 0.1%
https://lendingclub.com/browse/loanDetail.action?loan_id=685855181
 
< 0.1%
Other values (2936)2936
99.7%

Length

2021-06-21T11:44:21.235065image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://lendingclub.com/browse/loandetail.action?loan_id=685455011
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=684256861
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=684453681
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=685474851
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=685135681
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=683565561
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=685856141
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=686169191
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=685766541
 
< 0.1%
https://lendingclub.com/browse/loandetail.action?loan_id=684651241
 
< 0.1%
Other values (2936)2936
99.7%

Most occurring characters

ValueCountFrequency (%)
l14730
 
7.7%
n14730
 
7.7%
o14730
 
7.7%
t11784
 
6.2%
/11784
 
6.2%
i11784
 
6.2%
a11784
 
6.2%
e8838
 
4.6%
c8838
 
4.6%
s5892
 
3.1%
Other values (25)76592
40.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter135516
70.8%
Other Punctuation23568
 
12.3%
Decimal Number23564
 
12.3%
Uppercase Letter2946
 
1.5%
Connector Punctuation2946
 
1.5%
Math Symbol2946
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l14730
10.9%
n14730
10.9%
o14730
10.9%
t11784
8.7%
i11784
8.7%
a11784
8.7%
e8838
 
6.5%
c8838
 
6.5%
s5892
 
4.3%
d5892
 
4.3%
Other values (8)26514
19.6%
Decimal Number
ValueCountFrequency (%)
65318
22.6%
84024
17.1%
53112
13.2%
42553
10.8%
31804
 
7.7%
71525
 
6.5%
91331
 
5.6%
01330
 
5.6%
21303
 
5.5%
11264
 
5.4%
Other Punctuation
ValueCountFrequency (%)
/11784
50.0%
.5892
25.0%
:2946
 
12.5%
?2946
 
12.5%
Uppercase Letter
ValueCountFrequency (%)
D2946
100.0%
Connector Punctuation
ValueCountFrequency (%)
_2946
100.0%
Math Symbol
ValueCountFrequency (%)
=2946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin138462
72.3%
Common53024
 
27.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
l14730
10.6%
n14730
10.6%
o14730
10.6%
t11784
 
8.5%
i11784
 
8.5%
a11784
 
8.5%
e8838
 
6.4%
c8838
 
6.4%
s5892
 
4.3%
d5892
 
4.3%
Other values (9)29460
21.3%
Common
ValueCountFrequency (%)
/11784
22.2%
.5892
11.1%
65318
10.0%
84024
 
7.6%
53112
 
5.9%
:2946
 
5.6%
?2946
 
5.6%
_2946
 
5.6%
=2946
 
5.6%
42553
 
4.8%
Other values (6)8557
16.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII191486
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l14730
 
7.7%
n14730
 
7.7%
o14730
 
7.7%
t11784
 
6.2%
/11784
 
6.2%
i11784
 
6.2%
a11784
 
6.2%
e8838
 
4.6%
c8838
 
4.6%
s5892
 
3.1%
Other values (25)76592
40.0%

purpose
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct12
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
debt_consolidation
1731 
credit_card
718 
home_improvement
 
160
other
 
149
major_purchase
 
55
Other values (7)
 
133

Length

Max length18
Median length18
Mean length14.98574338
Min length3

Characters and Unicode

Total characters44148
Distinct characters22
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowdebt_consolidation
2nd rowsmall_business
3rd rowhome_improvement
4th rowdebt_consolidation
5th rowmajor_purchase

Common Values

ValueCountFrequency (%)
debt_consolidation1731
58.8%
credit_card718
24.4%
home_improvement160
 
5.4%
other149
 
5.1%
major_purchase55
 
1.9%
small_business33
 
1.1%
car31
 
1.1%
medical21
 
0.7%
vacation17
 
0.6%
house17
 
0.6%
Other values (2)14
 
0.5%

Length

2021-06-21T11:44:21.558105image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
debt_consolidation1731
58.8%
credit_card718
24.4%
home_improvement160
 
5.4%
other149
 
5.1%
major_purchase55
 
1.9%
small_business33
 
1.1%
car31
 
1.1%
medical21
 
0.7%
vacation17
 
0.6%
house17
 
0.6%
Other values (2)14
 
0.5%

Most occurring characters

ValueCountFrequency (%)
o5764
13.1%
d4919
11.1%
t4506
10.2%
i4424
10.0%
n3687
8.4%
c3291
7.5%
e3209
7.3%
_2698
 
6.1%
a2679
 
6.1%
s1935
 
4.4%
Other values (12)7036
15.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter41450
93.9%
Connector Punctuation2698
 
6.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o5764
13.9%
d4919
11.9%
t4506
10.9%
i4424
10.7%
n3687
8.9%
c3291
7.9%
e3209
7.7%
a2679
6.5%
s1935
 
4.7%
r1888
 
4.6%
Other values (11)5148
12.4%
Connector Punctuation
ValueCountFrequency (%)
_2698
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin41450
93.9%
Common2698
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o5764
13.9%
d4919
11.9%
t4506
10.9%
i4424
10.7%
n3687
8.9%
c3291
7.9%
e3209
7.7%
a2679
6.5%
s1935
 
4.7%
r1888
 
4.6%
Other values (11)5148
12.4%
Common
ValueCountFrequency (%)
_2698
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII44148
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o5764
13.1%
d4919
11.1%
t4506
10.2%
i4424
10.0%
n3687
8.4%
c3291
7.5%
e3209
7.3%
_2698
 
6.1%
a2679
 
6.1%
s1935
 
4.4%
Other values (12)7036
15.9%

title
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct12
Distinct (%)0.4%
Missing64
Missing (%)2.2%
Memory size23.1 KiB
Debt consolidation
1699 
Credit card refinancing
699 
Home improvement
 
156
Other
 
141
Major purchase
 
55
Other values (7)
 
132

Length

Max length23
Median length18
Mean length18.12144344
Min length5

Characters and Unicode

Total characters52226
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowDebt consolidation
2nd rowBusiness
3rd rowDebt consolidation
4th rowMajor purchase
5th rowDebt consolidation

Common Values

ValueCountFrequency (%)
Debt consolidation1699
57.7%
Credit card refinancing699
23.7%
Home improvement156
 
5.3%
Other141
 
4.8%
Major purchase55
 
1.9%
Business33
 
1.1%
Car financing30
 
1.0%
Medical expenses21
 
0.7%
Vacation17
 
0.6%
Home buying17
 
0.6%
Other values (2)14
 
0.5%
(Missing)64
 
2.2%

Length

2021-06-21T11:44:21.862968image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
debt1699
27.0%
consolidation1699
27.0%
credit699
11.1%
card699
11.1%
refinancing699
11.1%
home173
 
2.8%
improvement156
 
2.5%
other141
 
2.2%
purchase55
 
0.9%
major55
 
0.9%
Other values (12)210
 
3.3%

Most occurring characters

ValueCountFrequency (%)
n5870
11.2%
i5825
11.2%
o5538
10.6%
t4424
8.5%
e3910
 
7.5%
3403
 
6.5%
a3349
 
6.4%
c3233
 
6.2%
d3131
 
6.0%
r2548
 
4.9%
Other values (21)10995
21.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter45941
88.0%
Space Separator3403
 
6.5%
Uppercase Letter2882
 
5.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n5870
12.8%
i5825
12.7%
o5538
12.1%
t4424
9.6%
e3910
8.5%
a3349
7.3%
c3233
7.0%
d3131
6.8%
r2548
5.5%
s1895
 
4.1%
Other values (12)6218
13.5%
Uppercase Letter
ValueCountFrequency (%)
D1699
59.0%
C729
25.3%
H173
 
6.0%
O141
 
4.9%
M89
 
3.1%
B33
 
1.1%
V17
 
0.6%
G1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
3403
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin48823
93.5%
Common3403
 
6.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
n5870
12.0%
i5825
11.9%
o5538
11.3%
t4424
9.1%
e3910
8.0%
a3349
 
6.9%
c3233
 
6.6%
d3131
 
6.4%
r2548
 
5.2%
s1895
 
3.9%
Other values (20)9100
18.6%
Common
ValueCountFrequency (%)
3403
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII52226
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n5870
11.2%
i5825
11.2%
o5538
10.6%
t4424
8.5%
e3910
 
7.5%
3403
 
6.5%
a3349
 
6.4%
c3233
 
6.2%
d3131
 
6.0%
r2548
 
4.9%
Other values (21)10995
21.1%

zip_code
Categorical

HIGH CARDINALITY

Distinct629
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
300xx
 
34
112xx
 
34
750xx
 
32
606xx
 
32
770xx
 
30
Other values (624)
2784 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters14730
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique160 ?
Unique (%)5.4%

Sample

1st row190xx
2nd row577xx
3rd row605xx
4th row076xx
5th row174xx

Common Values

ValueCountFrequency (%)
300xx34
 
1.2%
112xx34
 
1.2%
750xx32
 
1.1%
606xx32
 
1.1%
770xx30
 
1.0%
945xx29
 
1.0%
117xx25
 
0.8%
917xx24
 
0.8%
104xx24
 
0.8%
921xx23
 
0.8%
Other values (619)2659
90.3%

Length

2021-06-21T11:44:22.174238image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
300xx34
 
1.2%
112xx34
 
1.2%
750xx32
 
1.1%
606xx32
 
1.1%
770xx30
 
1.0%
945xx29
 
1.0%
117xx25
 
0.8%
917xx24
 
0.8%
104xx24
 
0.8%
921xx23
 
0.8%
Other values (619)2659
90.3%

Most occurring characters

ValueCountFrequency (%)
x5892
40.0%
01335
 
9.1%
11091
 
7.4%
3994
 
6.7%
2972
 
6.6%
7881
 
6.0%
9786
 
5.3%
4768
 
5.2%
5675
 
4.6%
8674
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number8838
60.0%
Lowercase Letter5892
40.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
01335
15.1%
11091
12.3%
3994
11.2%
2972
11.0%
7881
10.0%
9786
8.9%
4768
8.7%
5675
7.6%
8674
7.6%
6662
7.5%
Lowercase Letter
ValueCountFrequency (%)
x5892
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common8838
60.0%
Latin5892
40.0%

Most frequent character per script

Common
ValueCountFrequency (%)
01335
15.1%
11091
12.3%
3994
11.2%
2972
11.0%
7881
10.0%
9786
8.9%
4768
8.7%
5675
7.6%
8674
7.6%
6662
7.5%
Latin
ValueCountFrequency (%)
x5892
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII14730
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
x5892
40.0%
01335
 
9.1%
11091
 
7.4%
3994
 
6.7%
2972
 
6.6%
7881
 
6.0%
9786
 
5.3%
4768
 
5.2%
5675
 
4.6%
8674
 
4.6%

addr_state
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct49
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
CA
357 
TX
247 
NY
238 
FL
197 
IL
 
106
Other values (44)
1801 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters5892
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPA
2nd rowSD
3rd rowIL
4th rowNJ
5th rowPA

Common Values

ValueCountFrequency (%)
CA357
 
12.1%
TX247
 
8.4%
NY238
 
8.1%
FL197
 
6.7%
IL106
 
3.6%
OH106
 
3.6%
VA103
 
3.5%
GA100
 
3.4%
MD99
 
3.4%
NJ96
 
3.3%
Other values (39)1297
44.0%

Length

2021-06-21T11:44:22.489796image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ca357
 
12.1%
tx247
 
8.4%
ny238
 
8.1%
fl197
 
6.7%
oh106
 
3.6%
il106
 
3.6%
va103
 
3.5%
ga100
 
3.4%
md99
 
3.4%
nj96
 
3.3%
Other values (39)1297
44.0%

Most occurring characters

ValueCountFrequency (%)
A979
16.6%
N648
11.0%
C602
10.2%
M434
 
7.4%
L388
 
6.6%
T370
 
6.3%
I300
 
5.1%
O288
 
4.9%
Y269
 
4.6%
X247
 
4.2%
Other values (14)1367
23.2%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter5892
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A979
16.6%
N648
11.0%
C602
10.2%
M434
 
7.4%
L388
 
6.6%
T370
 
6.3%
I300
 
5.1%
O288
 
4.9%
Y269
 
4.6%
X247
 
4.2%
Other values (14)1367
23.2%

Most occurring scripts

ValueCountFrequency (%)
Latin5892
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A979
16.6%
N648
11.0%
C602
10.2%
M434
 
7.4%
L388
 
6.6%
T370
 
6.3%
I300
 
5.1%
O288
 
4.9%
Y269
 
4.6%
X247
 
4.2%
Other values (14)1367
23.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII5892
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A979
16.6%
N648
11.0%
C602
10.2%
M434
 
7.4%
L388
 
6.6%
T370
 
6.3%
I300
 
5.1%
O288
 
4.9%
Y269
 
4.6%
X247
 
4.2%
Other values (14)1367
23.2%

dti
Real number (ℝ≥0)

Distinct1898
Distinct (%)64.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.44411745
Minimum0
Maximum51.2
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2021-06-21T11:44:22.624728image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile5.915
Q113.035
median18.905
Q325.58
95-th percentile34.395
Maximum51.2
Range51.2
Interquartile range (IQR)12.545

Descriptive statistics

Standard deviation8.628542991
Coefficient of variation (CV)0.4437611023
Kurtosis-0.562636739
Mean19.44411745
Median Absolute Deviation (MAD)6.24
Skewness0.1958927958
Sum57282.37
Variance74.45175414
MonotonicityNot monotonic
2021-06-21T11:44:22.781402image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
16.936
 
0.2%
25.436
 
0.2%
10.176
 
0.2%
23.266
 
0.2%
14.46
 
0.2%
20.546
 
0.2%
29.155
 
0.2%
21.65
 
0.2%
21.535
 
0.2%
8.515
 
0.2%
Other values (1888)2890
98.1%
ValueCountFrequency (%)
01
< 0.1%
0.251
< 0.1%
0.621
< 0.1%
0.631
< 0.1%
0.71
< 0.1%
0.761
< 0.1%
0.811
< 0.1%
0.941
< 0.1%
1.071
< 0.1%
1.141
< 0.1%
ValueCountFrequency (%)
51.21
< 0.1%
46.711
< 0.1%
39.981
< 0.1%
39.871
< 0.1%
39.841
< 0.1%
39.831
< 0.1%
39.711
< 0.1%
39.691
< 0.1%
39.561
< 0.1%
39.372
0.1%

earliest_cr_line
Categorical

HIGH CARDINALITY

Distinct426
Distinct (%)14.5%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
3-Aug
 
29
4-Sep
 
27
3-Sep
 
27
2-Sep
 
27
Nov-99
 
27
Other values (421)
2809 

Length

Max length6
Median length6
Mean length5.567888663
Min length5

Characters and Unicode

Total characters16403
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)2.5%

Sample

1st row3-Aug
2nd rowDec-99
3rd rowAug-00
4th row8-Sep
5th rowJun-98

Common Values

ValueCountFrequency (%)
3-Aug29
 
1.0%
4-Sep27
 
0.9%
3-Sep27
 
0.9%
2-Sep27
 
0.9%
Nov-9927
 
0.9%
3-Jul25
 
0.8%
4-Oct25
 
0.8%
4-Nov23
 
0.8%
3-Mar22
 
0.7%
Nov-0022
 
0.7%
Other values (416)2692
91.4%

Length

2021-06-21T11:44:23.133593image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3-aug29
 
1.0%
2-sep27
 
0.9%
4-sep27
 
0.9%
3-sep27
 
0.9%
nov-9927
 
0.9%
3-jul25
 
0.8%
4-oct25
 
0.8%
4-nov23
 
0.8%
nov-0022
 
0.7%
3-mar22
 
0.7%
Other values (416)2692
91.4%

Most occurring characters

ValueCountFrequency (%)
-2946
18.0%
91280
 
7.8%
u737
 
4.5%
e726
 
4.4%
a664
 
4.0%
J657
 
4.0%
8560
 
3.4%
p525
 
3.2%
c521
 
3.2%
A513
 
3.1%
Other values (23)7274
44.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter5892
35.9%
Decimal Number4619
28.2%
Dash Punctuation2946
18.0%
Uppercase Letter2946
18.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u737
12.5%
e726
12.3%
a664
11.3%
p525
8.9%
c521
8.8%
r472
8.0%
n424
7.2%
t297
 
5.0%
o287
 
4.9%
v287
 
4.9%
Other values (4)952
16.2%
Decimal Number
ValueCountFrequency (%)
91280
27.7%
8560
12.1%
0466
 
10.1%
1419
 
9.1%
4360
 
7.8%
3332
 
7.2%
2322
 
7.0%
5299
 
6.5%
7291
 
6.3%
6290
 
6.3%
Uppercase Letter
ValueCountFrequency (%)
J657
22.3%
A513
17.4%
M466
15.8%
O297
10.1%
S290
9.8%
N287
9.7%
D224
 
7.6%
F212
 
7.2%
Dash Punctuation
ValueCountFrequency (%)
-2946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin8838
53.9%
Common7565
46.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
u737
 
8.3%
e726
 
8.2%
a664
 
7.5%
J657
 
7.4%
p525
 
5.9%
c521
 
5.9%
A513
 
5.8%
r472
 
5.3%
M466
 
5.3%
n424
 
4.8%
Other values (12)3133
35.4%
Common
ValueCountFrequency (%)
-2946
38.9%
91280
16.9%
8560
 
7.4%
0466
 
6.2%
1419
 
5.5%
4360
 
4.8%
3332
 
4.4%
2322
 
4.3%
5299
 
4.0%
7291
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII16403
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
-2946
18.0%
91280
 
7.8%
u737
 
4.5%
e726
 
4.4%
a664
 
4.0%
J657
 
4.0%
8560
 
3.4%
p525
 
3.2%
c521
 
3.2%
A513
 
3.1%
Other values (23)7274
44.3%

last_pymnt_d
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct39
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
19-Jan
444 
19-Feb
284 
19-Mar
 
128
18-Dec
 
104
18-Mar
 
78
Other values (34)
1908 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters17676
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row19-Jan
2nd row16-Jun
3rd row17-Jun
4th row19-Feb
5th row16-Jul

Common Values

ValueCountFrequency (%)
19-Jan444
 
15.1%
19-Feb284
 
9.6%
19-Mar128
 
4.3%
18-Dec104
 
3.5%
18-Mar78
 
2.6%
17-Sep73
 
2.5%
17-Jan71
 
2.4%
17-Nov69
 
2.3%
17-May69
 
2.3%
17-Feb68
 
2.3%
Other values (29)1558
52.9%

Length

2021-06-21T11:44:24.039003image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
19-jan444
 
15.1%
19-feb284
 
9.6%
19-mar128
 
4.3%
18-dec104
 
3.5%
18-mar78
 
2.6%
17-sep73
 
2.5%
17-jan71
 
2.4%
17-nov69
 
2.3%
17-may69
 
2.3%
17-feb68
 
2.3%
Other values (29)1558
52.9%

Most occurring characters

ValueCountFrequency (%)
12946
16.7%
-2946
16.7%
a1073
 
6.1%
J925
 
5.2%
e860
 
4.9%
9856
 
4.8%
7785
 
4.4%
8753
 
4.3%
n751
 
4.2%
6552
 
3.1%
Other values (18)5229
29.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number5892
33.3%
Lowercase Letter5892
33.3%
Dash Punctuation2946
16.7%
Uppercase Letter2946
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a1073
18.2%
e860
14.6%
n751
12.7%
u510
8.7%
r477
8.1%
b436
7.4%
c400
 
6.8%
p357
 
6.1%
g176
 
3.0%
l174
 
3.0%
Other values (4)678
11.5%
Uppercase Letter
ValueCountFrequency (%)
J925
31.4%
M482
16.4%
F436
14.8%
A341
 
11.6%
D232
 
7.9%
S192
 
6.5%
N170
 
5.8%
O168
 
5.7%
Decimal Number
ValueCountFrequency (%)
12946
50.0%
9856
 
14.5%
7785
 
13.3%
8753
 
12.8%
6552
 
9.4%
Dash Punctuation
ValueCountFrequency (%)
-2946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common8838
50.0%
Latin8838
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a1073
12.1%
J925
 
10.5%
e860
 
9.7%
n751
 
8.5%
u510
 
5.8%
M482
 
5.5%
r477
 
5.4%
F436
 
4.9%
b436
 
4.9%
c400
 
4.5%
Other values (12)2488
28.2%
Common
ValueCountFrequency (%)
12946
33.3%
-2946
33.3%
9856
 
9.7%
7785
 
8.9%
8753
 
8.5%
6552
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII17676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12946
16.7%
-2946
16.7%
a1073
 
6.1%
J925
 
5.2%
e860
 
4.9%
9856
 
4.8%
7785
 
4.4%
8753
 
4.3%
n751
 
4.2%
6552
 
3.1%
Other values (18)5229
29.6%

last_pymnt_amnt
Real number (ℝ≥0)

HIGH CORRELATION

Distinct2678
Distinct (%)90.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4663.227026
Minimum0.03
Maximum35467.75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2021-06-21T11:44:24.178569image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum0.03
5-th percentile66.7125
Q1362.98
median842.235
Q36832.185
95-th percentile20262.56
Maximum35467.75
Range35467.72
Interquartile range (IQR)6469.205

Descriptive statistics

Standard deviation6855.29761
Coefficient of variation (CV)1.470075888
Kurtosis3.450675577
Mean4663.227026
Median Absolute Deviation (MAD)735.32
Skewness1.936828897
Sum13737866.82
Variance46995105.33
MonotonicityNot monotonic
2021-06-21T11:44:24.326720image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
465.2711
 
0.4%
507
 
0.2%
778.386
 
0.2%
459.585
 
0.2%
569.085
 
0.2%
482.225
 
0.2%
621.745
 
0.2%
275.755
 
0.2%
315.594
 
0.1%
544.614
 
0.1%
Other values (2668)2889
98.1%
ValueCountFrequency (%)
0.031
< 0.1%
0.141
< 0.1%
0.191
< 0.1%
0.261
< 0.1%
0.291
< 0.1%
0.341
< 0.1%
0.392
0.1%
0.41
< 0.1%
0.431
< 0.1%
0.561
< 0.1%
ValueCountFrequency (%)
35467.751
< 0.1%
35456.981
< 0.1%
35307.691
< 0.1%
35187.841
< 0.1%
34945.431
< 0.1%
34908.951
< 0.1%
34484.921
< 0.1%
34140.551
< 0.1%
33863.541
< 0.1%
33804.361
< 0.1%

next_pymnt_d
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)0.6%
Missing2610
Missing (%)88.6%
Memory size23.1 KiB
19-Apr
335 
19-Mar
 
1

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters2016
Distinct characters8
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row19-Apr
2nd row19-Apr
3rd row19-Apr
4th row19-Apr
5th row19-Apr

Common Values

ValueCountFrequency (%)
19-Apr335
 
11.4%
19-Mar1
 
< 0.1%
(Missing)2610
88.6%

Length

2021-06-21T11:44:24.633691image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-06-21T11:44:24.721438image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
ValueCountFrequency (%)
19-apr335
99.7%
19-mar1
 
0.3%

Most occurring characters

ValueCountFrequency (%)
1336
16.7%
9336
16.7%
-336
16.7%
r336
16.7%
A335
16.6%
p335
16.6%
M1
 
< 0.1%
a1
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number672
33.3%
Lowercase Letter672
33.3%
Dash Punctuation336
16.7%
Uppercase Letter336
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r336
50.0%
p335
49.9%
a1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1336
50.0%
9336
50.0%
Uppercase Letter
ValueCountFrequency (%)
A335
99.7%
M1
 
0.3%
Dash Punctuation
ValueCountFrequency (%)
-336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1008
50.0%
Latin1008
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r336
33.3%
A335
33.2%
p335
33.2%
M1
 
0.1%
a1
 
0.1%
Common
ValueCountFrequency (%)
1336
33.3%
9336
33.3%
-336
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII2016
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1336
16.7%
9336
16.7%
-336
16.7%
r336
16.7%
A335
16.6%
p335
16.6%
M1
 
< 0.1%
a1
 
< 0.1%

last_credit_pull_d
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct40
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
19-Mar
1287 
18-Dec
237 
19-Jan
166 
19-Feb
155 
18-Jul
 
95
Other values (35)
1006 

Length

Max length6
Median length6
Mean length6
Min length6

Characters and Unicode

Total characters17676
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row19-Mar
2nd row19-Mar
3rd row19-Mar
4th row19-Mar
5th row18-Mar

Common Values

ValueCountFrequency (%)
19-Mar1287
43.7%
18-Dec237
 
8.0%
19-Jan166
 
5.6%
19-Feb155
 
5.3%
18-Jul95
 
3.2%
18-Nov73
 
2.5%
18-Oct69
 
2.3%
18-Sep58
 
2.0%
18-Aug56
 
1.9%
18-Mar53
 
1.8%
Other values (30)697
23.7%

Length

2021-06-21T11:44:25.020839image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
19-mar1287
43.7%
18-dec237
 
8.0%
19-jan166
 
5.6%
19-feb155
 
5.3%
18-jul95
 
3.2%
18-nov73
 
2.5%
18-oct69
 
2.3%
18-sep58
 
2.0%
18-aug56
 
1.9%
18-mar53
 
1.8%
Other values (30)697
23.7%

Most occurring characters

ValueCountFrequency (%)
12946
16.7%
-2946
16.7%
a1675
9.5%
91608
9.1%
r1437
8.1%
M1429
8.1%
8812
 
4.6%
e640
 
3.6%
J443
 
2.5%
c436
 
2.5%
Other values (19)3304
18.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number5892
33.3%
Lowercase Letter5892
33.3%
Dash Punctuation2946
16.7%
Uppercase Letter2946
16.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a1675
28.4%
r1437
24.4%
e640
 
10.9%
c436
 
7.4%
n302
 
5.1%
u298
 
5.1%
b238
 
4.0%
p184
 
3.1%
t142
 
2.4%
l141
 
2.4%
Other values (4)399
 
6.8%
Uppercase Letter
ValueCountFrequency (%)
M1429
48.5%
J443
 
15.0%
D294
 
10.0%
F238
 
8.1%
A177
 
6.0%
O142
 
4.8%
N115
 
3.9%
S108
 
3.7%
Decimal Number
ValueCountFrequency (%)
12946
50.0%
91608
27.3%
8812
 
13.8%
7413
 
7.0%
6111
 
1.9%
52
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
-2946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common8838
50.0%
Latin8838
50.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a1675
19.0%
r1437
16.3%
M1429
16.2%
e640
 
7.2%
J443
 
5.0%
c436
 
4.9%
n302
 
3.4%
u298
 
3.4%
D294
 
3.3%
F238
 
2.7%
Other values (12)1646
18.6%
Common
ValueCountFrequency (%)
12946
33.3%
-2946
33.3%
91608
18.2%
8812
 
9.2%
7413
 
4.7%
6111
 
1.3%
52
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII17676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12946
16.7%
-2946
16.7%
a1675
9.5%
91608
9.1%
r1437
8.1%
M1429
8.1%
8812
 
4.6%
e640
 
3.6%
J443
 
2.5%
c436
 
2.5%
Other values (19)3304
18.7%

Time
Categorical

HIGH CARDINALITY

Distinct698
Distinct (%)23.7%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
3/23/2016 11:03
 
47
3/23/2016 8:47
 
44
3/23/2016 9:18
 
40
3/23/2016 9:53
 
40
3/23/2016 11:37
 
37
Other values (693)
2738 

Length

Max length15
Median length15
Mean length14.80040733
Min length14

Characters and Unicode

Total characters43602
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique181 ?
Unique (%)6.1%

Sample

1st row3/22/2016 9:51
2nd row3/22/2016 10:08
3rd row3/22/2016 10:08
4th row3/22/2016 10:08
5th row3/22/2016 10:08

Common Values

ValueCountFrequency (%)
3/23/2016 11:0347
 
1.6%
3/23/2016 8:4744
 
1.5%
3/23/2016 9:1840
 
1.4%
3/23/2016 9:5340
 
1.4%
3/23/2016 11:3737
 
1.3%
3/21/2016 14:1235
 
1.2%
3/23/2016 11:1434
 
1.2%
3/23/2016 10:1134
 
1.2%
3/21/2016 12:3532
 
1.1%
3/23/2016 8:5731
 
1.1%
Other values (688)2572
87.3%

Length

2021-06-21T11:44:25.356912image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
3/21/2016986
 
16.7%
3/22/2016882
 
15.0%
3/23/2016620
 
10.5%
3/18/2016458
 
7.8%
11:0352
 
0.9%
9:5347
 
0.8%
11:3746
 
0.8%
8:4746
 
0.8%
9:1844
 
0.7%
10:1141
 
0.7%
Other values (489)2670
45.3%

Most occurring characters

ValueCountFrequency (%)
18119
18.6%
27395
17.0%
/5892
13.5%
34557
10.5%
04071
9.3%
63505
8.0%
2946
 
6.8%
:2946
 
6.8%
41168
 
2.7%
5983
 
2.3%
Other values (3)2020
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number31818
73.0%
Other Punctuation8838
 
20.3%
Space Separator2946
 
6.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
18119
25.5%
27395
23.2%
34557
14.3%
04071
12.8%
63505
11.0%
41168
 
3.7%
5983
 
3.1%
8964
 
3.0%
9639
 
2.0%
7417
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/5892
66.7%
:2946
33.3%
Space Separator
ValueCountFrequency (%)
2946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common43602
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
18119
18.6%
27395
17.0%
/5892
13.5%
34557
10.5%
04071
9.3%
63505
8.0%
2946
 
6.8%
:2946
 
6.8%
41168
 
2.7%
5983
 
2.3%
Other values (3)2020
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII43602
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
18119
18.6%
27395
17.0%
/5892
13.5%
34557
10.5%
04071
9.3%
63505
8.0%
2946
 
6.8%
:2946
 
6.8%
41168
 
2.7%
5983
 
2.3%
Other values (3)2020
 
4.6%

emp_length
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct11
Distinct (%)1.5%
Missing2231
Missing (%)75.7%
Memory size23.1 KiB
10+ years
322 
3 years
50 
6 years
50 
< 1 year
49 
8 years
49 
Other values (6)
195 

Length

Max length9
Median length8
Mean length7.934265734
Min length6

Characters and Unicode

Total characters5673
Distinct characters18
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row< 1 year
2nd row10+ years
3rd row10+ years
4th row10+ years
5th row10+ years

Common Values

ValueCountFrequency (%)
10+ years322
 
10.9%
3 years50
 
1.7%
6 years50
 
1.7%
< 1 year49
 
1.7%
8 years49
 
1.7%
2 years48
 
1.6%
5 years48
 
1.6%
1 year25
 
0.8%
7 years25
 
0.8%
4 years25
 
0.8%
(Missing)2231
75.7%

Length

2021-06-21T11:44:25.632427image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
years641
43.3%
10322
21.8%
174
 
5.0%
year74
 
5.0%
350
 
3.4%
650
 
3.4%
49
 
3.3%
849
 
3.3%
548
 
3.2%
248
 
3.2%
Other values (3)74
 
5.0%

Most occurring characters

ValueCountFrequency (%)
764
13.5%
y715
12.6%
e715
12.6%
a715
12.6%
r715
12.6%
s641
11.3%
1396
7.0%
0322
5.7%
+322
5.7%
350
 
0.9%
Other values (8)318
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter3501
61.7%
Decimal Number1037
 
18.3%
Space Separator764
 
13.5%
Math Symbol371
 
6.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1396
38.2%
0322
31.1%
350
 
4.8%
650
 
4.8%
849
 
4.7%
548
 
4.6%
248
 
4.6%
425
 
2.4%
725
 
2.4%
924
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
y715
20.4%
e715
20.4%
a715
20.4%
r715
20.4%
s641
18.3%
Math Symbol
ValueCountFrequency (%)
+322
86.8%
<49
 
13.2%
Space Separator
ValueCountFrequency (%)
764
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin3501
61.7%
Common2172
38.3%

Most frequent character per script

Common
ValueCountFrequency (%)
764
35.2%
1396
18.2%
0322
14.8%
+322
14.8%
350
 
2.3%
650
 
2.3%
<49
 
2.3%
849
 
2.3%
548
 
2.2%
248
 
2.2%
Other values (3)74
 
3.4%
Latin
ValueCountFrequency (%)
y715
20.4%
e715
20.4%
a715
20.4%
r715
20.4%
s641
18.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII5673
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
764
13.5%
y715
12.6%
e715
12.6%
a715
12.6%
r715
12.6%
s641
11.3%
1396
7.0%
0322
5.7%
+322
5.7%
350
 
0.9%
Other values (8)318
5.6%

your_favoritearticle_today
Categorical

HIGH CARDINALITY
UNIFORM

Distinct2945
Distinct (%)100.0%
Missing1
Missing (%)< 0.1%
Memory size23.1 KiB
https://www.nytimes.com/2019/09/03/travel/prince-harry-travel-travalyst.html
 
1
https://abcnews.go.com/Politics/mike-pences-stay-trump-property-ireland-focus-senate/story?id=65407311
 
1
https://www.nytimes.com/2019/09/03/arts/music/justin-bieber-drug-use-instagram.html
 
1
https://www.cbsnews.com/news/roger-federer-us-open-meet-the-man-who-strings-roger-federers-tennis-rackets-ron-yu-2019-09-07/
 
1
https://www.cbsnews.com/video/mike-pence-defends-staying-at-trump-property-in-doonbeg-ireland/
 
1
Other values (2940)
2940 

Length

Max length325
Median length89
Mean length88.80848896
Min length35

Characters and Unicode

Total characters261541
Distinct characters76
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2945 ?
Unique (%)100.0%

Sample

1st rowhttps://www.reuters.com/article/us-tesla-crash-idUSKCN1VO22E
2nd rowhttps://www.irishtimes.com/business/economy/unemployment-falls-to-post-crash-low-of-5-2-1.4006266
3rd rowhttps://www.irishtimes.com/ /life-and-style/fashion/louise-kennedy-aw2019-long-coats-sparkling-tweed-dresses-and-emerald-knits-1.4006504
4th rowhttps://www.aljazeera.com/news/2019/09/north-korean-footballer-han-joins-italian-giants-juventus-190903164640390.html
5th rowhttps://www.bbc.co.uk/news/av/uk-scotland-49564244/uk-government-lawyer-says-proroguing-parliament-political-not-legal

Common Values

ValueCountFrequency (%)
https://www.nytimes.com/2019/09/03/travel/prince-harry-travel-travalyst.html1
 
< 0.1%
https://abcnews.go.com/Politics/mike-pences-stay-trump-property-ireland-focus-senate/story?id=654073111
 
< 0.1%
https://www.nytimes.com/2019/09/03/arts/music/justin-bieber-drug-use-instagram.html1
 
< 0.1%
https://www.cbsnews.com/news/roger-federer-us-open-meet-the-man-who-strings-roger-federers-tennis-rackets-ron-yu-2019-09-07/1
 
< 0.1%
https://www.cbsnews.com/video/mike-pence-defends-staying-at-trump-property-in-doonbeg-ireland/1
 
< 0.1%
https://www.bbc.co.uk/sport/football/495645501
 
< 0.1%
https://abcnews.go.com/International/wireStory/italy-police-detains-10-alleged-terrorism-financing-654499781
 
< 0.1%
https://www.cnn.com/2019/09/06/success/ceo-succession/index.html1
 
< 0.1%
https://www.aljazeera.com/news/2019/09/death-destruction-stalks-bahamas-wake-hurricane-dorian-190906022923964.html1
 
< 0.1%
http://www.bbc.co.uk/news/world-us-canada-496076841
 
< 0.1%
Other values (2935)2935
99.6%

Length

2021-06-21T11:44:26.016106image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
https://www.irishtimes.com31
 
1.0%
https://www.irishtimes.com/life-and-style/fashion/thanks-penneys-behind-the-scenes-as-the-fashion-empire-turns-50-1.39978681
 
< 0.1%
https://www.cnn.com/2019/09/05/us/taco-names-new-mexico-restaurant-trnd/index.html1
 
< 0.1%
https://www.nytimes.com/2019/09/06/realestate/so-your-house-wants-to-be-a-star.html1
 
< 0.1%
https://abcnews.go.com/us/wirestory/pain-scuba-diving-deaths-off-california-felt-globe-654525881
 
< 0.1%
https://www.bbc.co.uk/sport/football/495645501
 
< 0.1%
https://www.cnn.com/2019/09/06/success/ceo-succession/index.html1
 
< 0.1%
https://www.aljazeera.com/news/2019/09/death-destruction-stalks-bahamas-wake-hurricane-dorian-190906022923964.html1
 
< 0.1%
http://www.bbc.co.uk/news/world-us-canada-496076841
 
< 0.1%
https://www.nytimes.com/2019/09/03/travel/prince-harry-travel-travalyst.html1
 
< 0.1%
Other values (2936)2936
98.7%

Most occurring characters

ValueCountFrequency (%)
-19474
 
7.4%
e18119
 
6.9%
t17407
 
6.7%
s16793
 
6.4%
/15284
 
5.8%
i12917
 
4.9%
o12848
 
4.9%
n12353
 
4.7%
a11951
 
4.6%
r11819
 
4.5%
Other values (66)112576
43.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter190011
72.7%
Other Punctuation25673
 
9.8%
Decimal Number21795
 
8.3%
Dash Punctuation19474
 
7.4%
Uppercase Letter4060
 
1.6%
Control248
 
0.1%
Math Symbol171
 
0.1%
Connector Punctuation109
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e18119
 
9.5%
t17407
 
9.2%
s16793
 
8.8%
i12917
 
6.8%
o12848
 
6.8%
n12353
 
6.5%
a11951
 
6.3%
r11819
 
6.2%
w11023
 
5.8%
c9185
 
4.8%
Other values (16)55596
29.3%
Uppercase Letter
ValueCountFrequency (%)
S687
16.9%
N501
12.3%
C421
10.4%
U367
9.0%
K367
9.0%
V328
 
8.1%
A156
 
3.8%
I155
 
3.8%
O140
 
3.4%
Q102
 
2.5%
Other values (16)836
20.6%
Decimal Number
ValueCountFrequency (%)
04591
21.1%
13389
15.5%
93389
15.5%
22201
10.1%
41837
8.4%
51736
 
8.0%
61546
 
7.1%
31127
 
5.2%
71089
 
5.0%
8890
 
4.1%
Other Punctuation
ValueCountFrequency (%)
/15284
59.5%
.7319
28.5%
:2945
 
11.5%
?76
 
0.3%
%32
 
0.1%
&7
 
< 0.1%
;6
 
< 0.1%
#4
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
=83
48.5%
~82
48.0%
+6
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
-19474
100.0%
Control
ValueCountFrequency (%)
248
100.0%
Connector Punctuation
ValueCountFrequency (%)
_109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin194071
74.2%
Common67470
 
25.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e18119
 
9.3%
t17407
 
9.0%
s16793
 
8.7%
i12917
 
6.7%
o12848
 
6.6%
n12353
 
6.4%
a11951
 
6.2%
r11819
 
6.1%
w11023
 
5.7%
c9185
 
4.7%
Other values (42)59656
30.7%
Common
ValueCountFrequency (%)
-19474
28.9%
/15284
22.7%
.7319
 
10.8%
04591
 
6.8%
13389
 
5.0%
93389
 
5.0%
:2945
 
4.4%
22201
 
3.3%
41837
 
2.7%
51736
 
2.6%
Other values (14)5305
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII261541
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
-19474
 
7.4%
e18119
 
6.9%
t17407
 
6.7%
s16793
 
6.4%
/15284
 
5.8%
i12917
 
4.9%
o12848
 
4.9%
n12353
 
4.7%
a11951
 
4.6%
r11819
 
4.5%
Other values (66)112576
43.0%

url
Categorical

HIGH CARDINALITY
UNIFORM
UNIQUE

Distinct2946
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
wlservices.fr/css/webscr.php?cmd=_login-run&dispatch=5885d80a13c0db1f1ff80d546411d7f84f1036d8f209d3d19ebb6f4eeec8bd0e58f68c371b0c6dfb0c971e2b6492d5d658f68c371b0c6dfb0c971e2b6492d5d6
 
1
hagabloggen.nu/char/www.paypal.com/fr/
 
1
jennys.com.bd/Information/login.php
 
1
www.egitimogretimci.com/wp-admin/images/screenshots/index.htm
 
1
www.sanelyurdu.com/language/homebank.tsbbank.co.nz/SignOn.htm
 
1
Other values (2941)
2941 

Length

Max length683
Median length54
Mean length74.55838425
Min length10

Characters and Unicode

Total characters219649
Distinct characters85
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2946 ?
Unique (%)100.0%

Sample

1st rownobell.it/70ffb52d079109dca5664cce6f317373782/login.SkyPe.com/en/cgi-bin/verification/login/70ffb52d079109dca5664cce6f317373/index.php?cmd=_profile-ach&outdated_page_tmpl=p/gen/failed-to-load&nav=0.5.1&login_access=1322408526
2nd rowwww.dghjdgf.com/paypal.co.uk/cycgi-bin/webscrcmd=_home-customer&nav=1/loading.php
3rd rowserviciosbys.com/paypal.cgi.bin.get-into.herf.secure.dispatch35463256rzr321654641dsf654321874/href/href/href/secure/center/update/limit/seccure/4d7a1ff5c55825a2e632a679c2fd5353/
4th rowmail.printakid.com/www.online.americanexpress.com/index.html
5th rowthewhiskeydregs.com/wp-content/themes/widescreen/includes/temp/promocoessmiles/?84784787824HDJNDJDSJSHD//2724782784/

Common Values

ValueCountFrequency (%)
wlservices.fr/css/webscr.php?cmd=_login-run&dispatch=5885d80a13c0db1f1ff80d546411d7f84f1036d8f209d3d19ebb6f4eeec8bd0e58f68c371b0c6dfb0c971e2b6492d5d658f68c371b0c6dfb0c971e2b6492d5d61
 
< 0.1%
hagabloggen.nu/char/www.paypal.com/fr/1
 
< 0.1%
jennys.com.bd/Information/login.php1
 
< 0.1%
www.egitimogretimci.com/wp-admin/images/screenshots/index.htm1
 
< 0.1%
www.sanelyurdu.com/language/homebank.tsbbank.co.nz/SignOn.htm1
 
< 0.1%
service-giveaway-forum-kingyoza.tk/1
 
< 0.1%
www.ihr-einkauf.com/ie_bilder/Files/files/customer/login/logout/1
 
< 0.1%
bradtsics.com/zDcntrlde/webscr.php?cmd_=session.start&amp;sdr01=bWVAMjBkYXlzZHVsbC5kZQ==1
 
< 0.1%
promocaomembertamfidelidade.tk/1
 
< 0.1%
kk-samara.ru/fidelidade/-/tam.com.br/java/1
 
< 0.1%
Other values (2936)2936
99.7%

Length

2021-06-21T11:44:26.375366image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
login.html7
 
0.2%
b2b/new4
 
0.1%
b2b/index.htm4
 
0.1%
krotzon.biz/pcntrlde/webscr_prim.php?sdr01=a2fyaw4uagvlceb0lw9ubgluzs5kzq3
 
0.1%
krotzon.biz/pcntrlde/webscr_prim.php?sdr01=agvsz2eucg9ldhnjaeb0lw9ubgluzs5kzq3
 
0.1%
sepakbolaonline.com/wp-content/themes/redcarpet-3.0.6/safe/ib.nab.com.au2
 
0.1%
playnauth.com/img/apps/online2
 
0.1%
dazzletechnologies.com/images/worldwide/paypalworldwide.inc/cgi-bin/webscrcmd=_login-run/webscrcmd=_account-run/updates-paypal/confirm-paypal2
 
0.1%
krotzon.biz/pcntrlde/webscr_prim.php?sdr01=anvuz2jydw5uzw5adc1vbmxpbmuuzgu2
 
0.1%
krotzon.biz/pcntrlde/webscr_prim.php?sdr01=agvyymvydgtyyxrzy2htyxjadc1vbmxpbmuuzgu2
 
0.1%
Other values (2893)2942
99.0%

Most occurring characters

ValueCountFrequency (%)
e13387
 
6.1%
a11919
 
5.4%
.10223
 
4.7%
c10195
 
4.6%
o9865
 
4.5%
/9512
 
4.3%
i9148
 
4.2%
s8460
 
3.9%
n8042
 
3.7%
m7986
 
3.6%
Other values (75)120912
55.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter151139
68.8%
Decimal Number31168
 
14.2%
Other Punctuation22838
 
10.4%
Uppercase Letter9403
 
4.3%
Dash Punctuation2313
 
1.1%
Math Symbol1825
 
0.8%
Connector Punctuation930
 
0.4%
Space Separator27
 
< 0.1%
Open Punctuation3
 
< 0.1%
Close Punctuation3
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e13387
 
8.9%
a11919
 
7.9%
c10195
 
6.7%
o9865
 
6.5%
i9148
 
6.1%
s8460
 
5.6%
n8042
 
5.3%
m7986
 
5.3%
t7814
 
5.2%
r7736
 
5.1%
Other values (16)56587
37.4%
Uppercase Letter
ValueCountFrequency (%)
S527
 
5.6%
F487
 
5.2%
Z460
 
4.9%
I457
 
4.9%
A450
 
4.8%
B446
 
4.7%
C425
 
4.5%
E422
 
4.5%
V409
 
4.3%
L403
 
4.3%
Other values (16)4917
52.3%
Other Punctuation
ValueCountFrequency (%)
.10223
44.8%
/9512
41.6%
&1086
 
4.8%
?654
 
2.9%
;493
 
2.2%
\281
 
1.2%
%281
 
1.2%
'216
 
0.9%
:45
 
0.2%
,21
 
0.1%
Other values (3)26
 
0.1%
Decimal Number
ValueCountFrequency (%)
14008
12.9%
53554
11.4%
33519
11.3%
23430
11.0%
83393
10.9%
03288
10.5%
43045
9.8%
62593
8.3%
92376
7.6%
71962
6.3%
Math Symbol
ValueCountFrequency (%)
=1716
94.0%
~107
 
5.9%
+2
 
0.1%
Open Punctuation
ValueCountFrequency (%)
(2
66.7%
[1
33.3%
Close Punctuation
ValueCountFrequency (%)
)2
66.7%
]1
33.3%
Dash Punctuation
ValueCountFrequency (%)
-2313
100.0%
Connector Punctuation
ValueCountFrequency (%)
_930
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin160542
73.1%
Common59107
 
26.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e13387
 
8.3%
a11919
 
7.4%
c10195
 
6.4%
o9865
 
6.1%
i9148
 
5.7%
s8460
 
5.3%
n8042
 
5.0%
m7986
 
5.0%
t7814
 
4.9%
r7736
 
4.8%
Other values (42)65990
41.1%
Common
ValueCountFrequency (%)
.10223
17.3%
/9512
16.1%
14008
 
6.8%
53554
 
6.0%
33519
 
6.0%
23430
 
5.8%
83393
 
5.7%
03288
 
5.6%
43045
 
5.2%
62593
 
4.4%
Other values (23)12542
21.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII219649
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e13387
 
6.1%
a11919
 
5.4%
.10223
 
4.7%
c10195
 
4.6%
o9865
 
4.5%
/9512
 
4.3%
i9148
 
4.2%
s8460
 
3.9%
n8042
 
3.7%
m7986
 
3.6%
Other values (75)120912
55.0%

Email
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct1921
Distinct (%)99.0%
Missing1005
Missing (%)34.1%
Memory size23.1 KiB
na
 
4
dapcukhammam@gmail.com
 
3
nandkishor@arpanbloodbank.org
 
3
bloodbank.ahakp@gmail.com
 
2
bloodbankkanchipuram@gmail.com
 
2
Other values (1916)
1927 

Length

Max length76
Median length23
Mean length25.05203503
Min length2

Characters and Unicode

Total characters48626
Distinct characters68
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1905 ?
Unique (%)98.1%

Sample

1st rowmstephenson@fernandez.com
2nd rowhduke@hotmail.com
3rd rowpallen@yahoo.com
4th rowriverarebecca@gmail.com
5th rowmstephens@davidson-herman.com

Common Values

ValueCountFrequency (%)
na4
 
0.1%
dapcukhammam@gmail.com3
 
0.1%
nandkishor@arpanbloodbank.org3
 
0.1%
bloodbank.ahakp@gmail.com2
 
0.1%
bloodbankkanchipuram@gmail.com2
 
0.1%
vivekanandabloodbank@gmail.com2
 
0.1%
drnkbhatia@yahoo.com2
 
0.1%
msibloodbank@gmail.com2
 
0.1%
bloodbank.rtgh@gmail.com2
 
0.1%
bloodbank@parashospitals.com2
 
0.1%
Other values (1911)1917
65.1%
(Missing)1005
34.1%

Length

2021-06-21T11:44:26.815118image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
nandkishor@arpanbloodbank.org4
 
0.2%
na4
 
0.2%
dapcukhammam@gmail.com3
 
0.1%
2
 
0.1%
mgmhbloodbank@gmail.com2
 
0.1%
drrema_m@apollohospital.co2
 
0.1%
indian2
 
0.1%
msibloodbank@gmail.com2
 
0.1%
wgbloodbank@gmail.com2
 
0.1%
kalibloodbank@gmail.com2
 
0.1%
Other values (2028)2045
98.8%

Most occurring characters

ValueCountFrequency (%)
a5178
 
10.6%
o4882
 
10.0%
m3988
 
8.2%
i3113
 
6.4%
l3049
 
6.3%
c2663
 
5.5%
.2393
 
4.9%
n2263
 
4.7%
@2052
 
4.2%
b2042
 
4.2%
Other values (58)17003
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter42685
87.8%
Other Punctuation4574
 
9.4%
Decimal Number969
 
2.0%
Space Separator162
 
0.3%
Connector Punctuation95
 
0.2%
Dash Punctuation89
 
0.2%
Uppercase Letter46
 
0.1%
Control6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a5178
12.1%
o4882
11.4%
m3988
 
9.3%
i3113
 
7.3%
l3049
 
7.1%
c2663
 
6.2%
n2263
 
5.3%
b2042
 
4.8%
r2030
 
4.8%
g1774
 
4.2%
Other values (16)11703
27.4%
Uppercase Letter
ValueCountFrequency (%)
B6
 
13.0%
A4
 
8.7%
O3
 
6.5%
N3
 
6.5%
M3
 
6.5%
V2
 
4.3%
G2
 
4.3%
H2
 
4.3%
L2
 
4.3%
D2
 
4.3%
Other values (11)17
37.0%
Decimal Number
ValueCountFrequency (%)
1151
15.6%
0148
15.3%
2137
14.1%
9124
12.8%
876
7.8%
573
7.5%
370
7.2%
668
7.0%
463
6.5%
759
 
6.1%
Other Punctuation
ValueCountFrequency (%)
.2393
52.3%
@2052
44.9%
,124
 
2.7%
/2
 
< 0.1%
&1
 
< 0.1%
#1
 
< 0.1%
;1
 
< 0.1%
Dash Punctuation
ValueCountFrequency (%)
-89
100.0%
Connector Punctuation
ValueCountFrequency (%)
_95
100.0%
Space Separator
ValueCountFrequency (%)
162
100.0%
Control
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin42731
87.9%
Common5895
 
12.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a5178
12.1%
o4882
11.4%
m3988
 
9.3%
i3113
 
7.3%
l3049
 
7.1%
c2663
 
6.2%
n2263
 
5.3%
b2042
 
4.8%
r2030
 
4.8%
g1774
 
4.2%
Other values (37)11749
27.5%
Common
ValueCountFrequency (%)
.2393
40.6%
@2052
34.8%
162
 
2.7%
1151
 
2.6%
0148
 
2.5%
2137
 
2.3%
9124
 
2.1%
,124
 
2.1%
_95
 
1.6%
-89
 
1.5%
Other values (11)420
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII48626
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a5178
 
10.6%
o4882
 
10.0%
m3988
 
8.2%
i3113
 
6.4%
l3049
 
6.3%
c2663
 
5.5%
.2393
 
4.9%
n2263
 
4.7%
@2052
 
4.2%
b2042
 
4.2%
Other values (58)17003
35.0%

homeaddress
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct2629
Distinct (%)100.0%
Missing317
Missing (%)10.8%
Memory size23.1 KiB
13590 Northdale Blvd Ste 300 Rogers, MN 55374 US
 
1
13042 Fair Lakes Shopping Ctr Fairfax, VA 22033 US
 
1
7600 Cypress Creek Pkwy Houston, TX 77070 US
 
1
4130 Tuscarawas St W Canton, OH 44708 US
 
1
5550 Wilshire Blvd Ste 101B Los Angeles, CA 90036 US
 
1
Other values (2624)
2624 

Length

Max length75
Median length43
Mean length43.7360213
Min length30

Characters and Unicode

Total characters114982
Distinct characters69
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2629 ?
Unique (%)100.0%

Sample

1st row346 W Magnolia Ave Auburn, AL 36832 US
2nd row300 20th St S Birmingham, AL 35233 US
3rd row3220 Morrow Rd Birmingham, AL 35235 US
4th row4719 Highway 280 Birmingham, AL 35242 US
5th row1821 Cherokee Ave SW Cullman, AL 35055 US

Common Values

ValueCountFrequency (%)
13590 Northdale Blvd Ste 300 Rogers, MN 55374 US1
 
< 0.1%
13042 Fair Lakes Shopping Ctr Fairfax, VA 22033 US1
 
< 0.1%
7600 Cypress Creek Pkwy Houston, TX 77070 US1
 
< 0.1%
4130 Tuscarawas St W Canton, OH 44708 US1
 
< 0.1%
5550 Wilshire Blvd Ste 101B Los Angeles, CA 90036 US1
 
< 0.1%
4774 E Grant Rd Tucson, AZ 85712 US1
 
< 0.1%
14383 Newbrook Dr Suite 100 Chantilly, VA 20151 US1
 
< 0.1%
5107 N Belt Hwy Ste 101 Saint Joseph, MO 64506 US1
 
< 0.1%
1787 Blowing Rock Rd Ste A Boone, NC 28607 US1
 
< 0.1%
6415 N Illinois St Fairview Heights, IL 62208 US1
 
< 0.1%
Other values (2619)2619
88.9%
(Missing)317
 
10.8%

Length

2021-06-21T11:44:27.175515image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
us2652
 
11.4%
ste871
 
3.7%
rd565
 
2.4%
st445
 
1.9%
ca421
 
1.8%
ave416
 
1.8%
blvd332
 
1.4%
n257
 
1.1%
w252
 
1.1%
s240
 
1.0%
Other values (7234)16791
72.2%

Most occurring characters

ValueCountFrequency (%)
20613
 
17.9%
e5726
 
5.0%
S5014
 
4.4%
04644
 
4.0%
14392
 
3.8%
t4041
 
3.5%
a4026
 
3.5%
n3346
 
2.9%
o3228
 
2.8%
r3218
 
2.8%
Other values (59)56734
49.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter43155
37.5%
Decimal Number26024
22.6%
Uppercase Letter22427
19.5%
Space Separator20613
17.9%
Other Punctuation2721
 
2.4%
Dash Punctuation42
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S5014
22.4%
U2794
12.5%
A1853
 
8.3%
C1505
 
6.7%
N1089
 
4.9%
R971
 
4.3%
B901
 
4.0%
M870
 
3.9%
L775
 
3.5%
W763
 
3.4%
Other values (16)5892
26.3%
Lowercase Letter
ValueCountFrequency (%)
e5726
13.3%
t4041
9.4%
a4026
9.3%
n3346
 
7.8%
o3228
 
7.5%
r3218
 
7.5%
l3117
 
7.2%
i2935
 
6.8%
d2088
 
4.8%
s1908
 
4.4%
Other values (16)9522
22.1%
Decimal Number
ValueCountFrequency (%)
04644
17.8%
14392
16.9%
23030
11.6%
32428
9.3%
52338
9.0%
42277
8.7%
71823
 
7.0%
61806
 
6.9%
91679
 
6.5%
81607
 
6.2%
Other Punctuation
ValueCountFrequency (%)
,2633
96.8%
.43
 
1.6%
#34
 
1.2%
&9
 
0.3%
/2
 
0.1%
Space Separator
ValueCountFrequency (%)
20613
100.0%
Dash Punctuation
ValueCountFrequency (%)
-42
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin65582
57.0%
Common49400
43.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e5726
 
8.7%
S5014
 
7.6%
t4041
 
6.2%
a4026
 
6.1%
n3346
 
5.1%
o3228
 
4.9%
r3218
 
4.9%
l3117
 
4.8%
i2935
 
4.5%
U2794
 
4.3%
Other values (42)28137
42.9%
Common
ValueCountFrequency (%)
20613
41.7%
04644
 
9.4%
14392
 
8.9%
23030
 
6.1%
,2633
 
5.3%
32428
 
4.9%
52338
 
4.7%
42277
 
4.6%
71823
 
3.7%
61806
 
3.7%
Other values (7)3416
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII114982
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
20613
 
17.9%
e5726
 
5.0%
S5014
 
4.4%
04644
 
4.0%
14392
 
3.8%
t4041
 
3.5%
a4026
 
3.5%
n3346
 
2.9%
o3228
 
2.8%
r3218
 
2.8%
Other values (59)56734
49.3%

latitude
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct2629
Distinct (%)100.0%
Missing317
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean37.51597903
Minimum25.4790088
Maximum48.785206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size23.1 KiB
2021-06-21T11:44:27.323571image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum25.4790088
5-th percentile28.48828107
Q133.87653522
median38.89808218
Q340.81312458
95-th percentile44.82209479
Maximum48.785206
Range23.3061972
Interquartile range (IQR)6.93658936

Descriptive statistics

Standard deviation4.749089461
Coefficient of variation (CV)0.1265884453
Kurtosis-0.345125694
Mean37.51597903
Median Absolute Deviation (MAD)3.02758465
Skewness-0.4603449143
Sum98629.50888
Variance22.55385071
MonotonicityNot monotonic
2021-06-21T11:44:27.491895image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.455111
 
< 0.1%
34.986509311
 
< 0.1%
41.250955681
 
< 0.1%
34.021455981
 
< 0.1%
41.0253491
 
< 0.1%
39.854842881
 
< 0.1%
42.563593311
 
< 0.1%
36.767951071
 
< 0.1%
38.957765061
 
< 0.1%
33.47225951
 
< 0.1%
Other values (2619)2619
88.9%
(Missing)317
 
10.8%
ValueCountFrequency (%)
25.47900881
< 0.1%
25.58963081
< 0.1%
25.62649661
< 0.1%
25.657060491
< 0.1%
25.684546061
< 0.1%
25.68626341
< 0.1%
25.699524791
< 0.1%
25.749186841
< 0.1%
25.749312191
< 0.1%
25.76924161
< 0.1%
ValueCountFrequency (%)
48.7852061
< 0.1%
48.453331931
< 0.1%
48.151148261
< 0.1%
47.909533891
< 0.1%
47.829798991
< 0.1%
47.82068431
< 0.1%
47.754703391
< 0.1%
47.721877961
< 0.1%
47.711843931
< 0.1%
47.70698921
< 0.1%

longitude
Real number (ℝ)

HIGH CORRELATION
MISSING

Distinct2629
Distinct (%)100.0%
Missing317
Missing (%)10.8%
Infinite0
Infinite (%)0.0%
Mean-92.49028662
Minimum-124.1836109
Maximum-68.75374997
Zeros0
Zeros (%)0.0%
Negative2629
Negative (%)89.2%
Memory size23.1 KiB
2021-06-21T11:44:27.646449image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Quantile statistics

Minimum-124.1836109
5-th percentile-121.9802342
Q1-105.0956733
median-87.18085139
Q3-78.879958
95-th percentile-73.58385376
Maximum-68.75374997
Range55.42986093
Interquartile range (IQR)26.2157153

Descriptive statistics

Standard deviation16.57861583
Coefficient of variation (CV)-0.1792471019
Kurtosis-1.042722021
Mean-92.49028662
Median Absolute Deviation (MAD)10.11861236
Skewness-0.6151661838
Sum-243156.9635
Variance274.850503
MonotonicityNot monotonic
2021-06-21T11:44:27.796982image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-80.038908021
 
< 0.1%
-89.528710611
 
< 0.1%
-70.799091991
 
< 0.1%
-82.734444031
 
< 0.1%
-71.3623171
 
< 0.1%
-97.463279191
 
< 0.1%
-102.12335291
 
< 0.1%
-77.174547941
 
< 0.1%
-78.8799581
 
< 0.1%
-95.6164571
 
< 0.1%
Other values (2619)2619
88.9%
(Missing)317
 
10.8%
ValueCountFrequency (%)
-124.18361091
< 0.1%
-123.2791241
< 0.1%
-123.19935971
< 0.1%
-123.0739791
< 0.1%
-123.07236811
< 0.1%
-123.04315941
< 0.1%
-123.03932721
< 0.1%
-122.99643731
< 0.1%
-122.9826371
< 0.1%
-122.93510631
< 0.1%
ValueCountFrequency (%)
-68.753749971
< 0.1%
-69.788595161
< 0.1%
-70.2666721
< 0.1%
-70.2956351
< 0.1%
-70.329753351
< 0.1%
-70.337845031
< 0.1%
-70.71107981
< 0.1%
-70.799091991
< 0.1%
-70.88003231
< 0.1%
-70.891196011
< 0.1%

PHONE
Categorical

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct24
Distinct (%)3.4%
Missing2231
Missing (%)75.7%
Memory size23.1 KiB
#ERROR!
74 
40.67.8555
49 
07-98 9555
49 
2125557818
49 
2035552570
 
25
Other values (19)
469 

Length

Max length14
Median length10
Mean length10.37622378
Min length7

Characters and Unicode

Total characters7419
Distinct characters20
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row(91) 555 22 82
2nd row2125557818
3rd row26.47.1555
4th row#ERROR!
5th row6265557265

Common Values

ValueCountFrequency (%)
#ERROR!74
 
2.5%
40.67.855549
 
1.7%
07-98 955549
 
1.7%
212555781849
 
1.7%
203555257025
 
0.8%
20.16.155525
 
0.8%
212555150025
 
0.8%
(1) 47.55.655525
 
0.8%
03 9520 455525
 
0.8%
(91) 555 22 8225
 
0.8%
Other values (14)344
 
11.7%
(Missing)2231
75.7%

Length

2021-06-21T11:44:28.135319image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
error74
 
7.0%
9149
 
4.6%
955549
 
4.6%
212555781849
 
4.6%
55549
 
4.6%
07-9849
 
4.6%
40.67.855549
 
4.6%
650555138625
 
2.4%
650555680925
 
2.4%
212555150025
 
2.4%
Other values (25)616
58.2%

Most occurring characters

ValueCountFrequency (%)
52489
33.5%
2665
 
9.0%
1516
 
7.0%
0496
 
6.7%
6397
 
5.4%
8394
 
5.3%
7346
 
4.7%
344
 
4.6%
9319
 
4.3%
.248
 
3.3%
Other values (10)1205
16.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number5967
80.4%
Other Punctuation396
 
5.3%
Uppercase Letter370
 
5.0%
Space Separator344
 
4.6%
Dash Punctuation146
 
2.0%
Open Punctuation98
 
1.3%
Close Punctuation98
 
1.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
52489
41.7%
2665
 
11.1%
1516
 
8.6%
0496
 
8.3%
6397
 
6.7%
8394
 
6.6%
7346
 
5.8%
9319
 
5.3%
4221
 
3.7%
3124
 
2.1%
Other Punctuation
ValueCountFrequency (%)
.248
62.6%
#74
 
18.7%
!74
 
18.7%
Uppercase Letter
ValueCountFrequency (%)
R222
60.0%
E74
 
20.0%
O74
 
20.0%
Open Punctuation
ValueCountFrequency (%)
(98
100.0%
Close Punctuation
ValueCountFrequency (%)
)98
100.0%
Space Separator
ValueCountFrequency (%)
344
100.0%
Dash Punctuation
ValueCountFrequency (%)
-146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common7049
95.0%
Latin370
 
5.0%

Most frequent character per script

Common
ValueCountFrequency (%)
52489
35.3%
2665
 
9.4%
1516
 
7.3%
0496
 
7.0%
6397
 
5.6%
8394
 
5.6%
7346
 
4.9%
344
 
4.9%
9319
 
4.5%
.248
 
3.5%
Other values (7)835
 
11.8%
Latin
ValueCountFrequency (%)
R222
60.0%
E74
 
20.0%
O74
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII7419
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
52489
33.5%
2665
 
9.0%
1516
 
7.0%
0496
 
6.7%
6397
 
5.4%
8394
 
5.3%
7346
 
4.7%
344
 
4.6%
9319
 
4.3%
.248
 
3.3%
Other values (10)1205
16.2%

officeaddress
Categorical

HIGH CARDINALITY
MISSING
UNIFORM

Distinct2331
Distinct (%)96.8%
Missing539
Missing (%)18.3%
Memory size23.1 KiB
1004 S. Olde Oneida St., Appleton, Wisconsin, 54915
 
3
445 St. Paul St., Rochester, New York, 14605
 
3
5905 S. Kirkman Rd., Orlando, Florida, 32819
 
2
21 E. Main Street, Cortez, Colorado, 81321
 
2
1249 Wicker Dr., Raleigh, North Carolina, 27604
 
2
Other values (2326)
2395 

Length

Max length74
Median length45
Mean length45.198172
Min length8

Characters and Unicode

Total characters108792
Distinct characters78
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2257 ?
Unique (%)93.8%

Sample

1st rowPO Box 4653, Stockton, California, 95204
2nd row157 Adams St., Stockton, California, 95204
3rd row1950 W Freemont, Stockton, California, 95203
4th row102 S. State St., Ukiah, California, 95482
5th row13011 Newport Ave. #100, Tustin, California, 92780

Common Values

ValueCountFrequency (%)
1004 S. Olde Oneida St., Appleton, Wisconsin, 549153
 
0.1%
445 St. Paul St., Rochester, New York, 146053
 
0.1%
5905 S. Kirkman Rd., Orlando, Florida, 328192
 
0.1%
21 E. Main Street, Cortez, Colorado, 813212
 
0.1%
1249 Wicker Dr., Raleigh, North Carolina, 276042
 
0.1%
347 S. Pierre St., Pierre, South Dakota, 575012
 
0.1%
707 E. Minnehaha, St. Paul, Minnesota, 551062
 
0.1%
36 East Cross Street, Baltimore, Maryland, 212302
 
0.1%
419 E. 6th St., Austin, Texas, 787012
 
0.1%
4246 North Buffalo Rd., Orchard Park, New York, 141272
 
0.1%
Other values (2321)2385
81.0%
(Missing)539
 
18.3%

Length

2021-06-21T11:44:28.485358image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
st851
 
5.0%
ave369
 
2.2%
california290
 
1.7%
new241
 
1.4%
rd236
 
1.4%
colorado196
 
1.2%
washington191
 
1.1%
n191
 
1.1%
e170
 
1.0%
oregon158
 
0.9%
Other values (5521)14034
82.9%

Most occurring characters

ValueCountFrequency (%)
14527
 
13.4%
,7235
 
6.7%
a6214
 
5.7%
e5085
 
4.7%
o4916
 
4.5%
n4898
 
4.5%
i4406
 
4.0%
r3938
 
3.6%
t3935
 
3.6%
l3555
 
3.3%
Other values (68)50083
46.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter51928
47.7%
Decimal Number20642
 
19.0%
Space Separator14527
 
13.4%
Uppercase Letter12059
 
11.1%
Other Punctuation9535
 
8.8%
Dash Punctuation66
 
0.1%
Open Punctuation15
 
< 0.1%
Close Punctuation15
 
< 0.1%
Other Symbol4
 
< 0.1%
Modifier Symbol1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S1842
15.3%
C1234
 
10.2%
M897
 
7.4%
W829
 
6.9%
A748
 
6.2%
P721
 
6.0%
B721
 
6.0%
N712
 
5.9%
R527
 
4.4%
O501
 
4.2%
Other values (16)3327
27.6%
Lowercase Letter
ValueCountFrequency (%)
a6214
12.0%
e5085
9.8%
o4916
9.5%
n4898
9.4%
i4406
8.5%
r3938
 
7.6%
t3935
 
7.6%
l3555
 
6.8%
s2696
 
5.2%
d1869
 
3.6%
Other values (16)10416
20.1%
Decimal Number
ValueCountFrequency (%)
13418
16.6%
03223
15.6%
22534
12.3%
31928
9.3%
41873
9.1%
51806
8.7%
91606
7.8%
81474
7.1%
71451
7.0%
61329
 
6.4%
Other Punctuation
ValueCountFrequency (%)
,7235
75.9%
.2156
 
22.6%
#85
 
0.9%
/22
 
0.2%
'17
 
0.2%
@8
 
0.1%
&5
 
0.1%
?4
 
< 0.1%
"2
 
< 0.1%
:1
 
< 0.1%
Space Separator
ValueCountFrequency (%)
14527
100.0%
Dash Punctuation
ValueCountFrequency (%)
-66
100.0%
Open Punctuation
ValueCountFrequency (%)
(15
100.0%
Close Punctuation
ValueCountFrequency (%)
)15
100.0%
Modifier Symbol
ValueCountFrequency (%)
`1
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin63987
58.8%
Common44805
41.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a6214
 
9.7%
e5085
 
7.9%
o4916
 
7.7%
n4898
 
7.7%
i4406
 
6.9%
r3938
 
6.2%
t3935
 
6.1%
l3555
 
5.6%
s2696
 
4.2%
d1869
 
2.9%
Other values (42)22475
35.1%
Common
ValueCountFrequency (%)
14527
32.4%
,7235
16.1%
13418
 
7.6%
03223
 
7.2%
22534
 
5.7%
.2156
 
4.8%
31928
 
4.3%
41873
 
4.2%
51806
 
4.0%
91606
 
3.6%
Other values (16)4499
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII108788
> 99.9%
Specials4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14527
 
13.4%
,7235
 
6.7%
a6214
 
5.7%
e5085
 
4.7%
o4916
 
4.5%
n4898
 
4.5%
i4406
 
4.1%
r3938
 
3.6%
t3935
 
3.6%
l3555
 
3.3%
Other values (67)50079
46.0%
Specials
ValueCountFrequency (%)
4
100.0%

website
Categorical

HIGH CARDINALITY
MISSING

Distinct1369
Distinct (%)57.1%
Missing547
Missing (%)18.6%
Memory size23.1 KiB
-
557 
http://www.rockbottom.com/
 
34
http://www.bjsbrewhouse.com/
 
28
http://www.mcmenaminspubs.com/
 
28
http://www.hopsrestaurants.com/
 
26
Other values (1364)
1726 

Length

Max length145
Median length31
Mean length57.03834931
Min length12

Characters and Unicode

Total characters136835
Distinct characters70
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1183 ?
Unique (%)49.3%

Sample

1st rowhttp://www.valleybrew.com/
2nd rowhttp://www.valleybrew.com/
3rd rowhttp://www.valleybrew.com/
4th rowhttp://www.ukiahbrewingco.com/
5th rowhttp://www.tustinbrewery.com/

Common Values

ValueCountFrequency (%)
- 557
 
18.9%
http://www.rockbottom.com/34
 
1.2%
http://www.bjsbrewhouse.com/28
 
1.0%
http://www.mcmenaminspubs.com/28
 
1.0%
http://www.hopsrestaurants.com/26
 
0.9%
http://www.gordonbiersch.com/23
 
0.8%
http://www.gcfb.net/16
 
0.5%
http://www.oggis.com/15
 
0.5%
http://www.theram.com/15
 
0.5%
http://www.mcmenamins.com/14
 
0.5%
Other values (1359)1643
55.8%
(Missing)547
 
18.6%

Length

2021-06-21T11:44:28.871659image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
557
 
23.2%
http://www.rockbottom.com34
 
1.4%
http://www.bjsbrewhouse.com28
 
1.2%
http://www.mcmenaminspubs.com28
 
1.2%
http://www.hopsrestaurants.com26
 
1.1%
http://www.gordonbiersch.com23
 
1.0%
http://www.gcfb.net16
 
0.7%
http://www.theram.com15
 
0.6%
http://www.oggis.com15
 
0.6%
http://www.mcmenamins.com14
 
0.6%
Other values (1361)1646
68.5%

Most occurring characters

ValueCountFrequency (%)
80212
58.6%
w6364
 
4.7%
/5579
 
4.1%
t4982
 
3.6%
.3757
 
2.7%
e3464
 
2.5%
o3335
 
2.4%
r2820
 
2.1%
h2664
 
1.9%
c2649
 
1.9%
Other values (60)21009
 
15.4%

Most occurring categories

ValueCountFrequency (%)
Space Separator80212
58.6%
Lowercase Letter44396
32.4%
Other Punctuation11176
 
8.2%
Dash Punctuation649
 
0.5%
Decimal Number232
 
0.2%
Uppercase Letter119
 
0.1%
Math Symbol28
 
< 0.1%
Connector Punctuation23
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w6364
14.3%
t4982
11.2%
e3464
 
7.8%
o3335
 
7.5%
r2820
 
6.4%
h2664
 
6.0%
c2649
 
6.0%
m2552
 
5.7%
p2461
 
5.5%
a1743
 
3.9%
Other values (16)11362
25.6%
Uppercase Letter
ValueCountFrequency (%)
B20
16.8%
C17
14.3%
H14
11.8%
T9
 
7.6%
S8
 
6.7%
A7
 
5.9%
L6
 
5.0%
R5
 
4.2%
P5
 
4.2%
M4
 
3.4%
Other values (13)24
20.2%
Decimal Number
ValueCountFrequency (%)
240
17.2%
139
16.8%
530
12.9%
026
11.2%
621
9.1%
718
7.8%
418
7.8%
816
 
6.9%
914
 
6.0%
310
 
4.3%
Other Punctuation
ValueCountFrequency (%)
/5579
49.9%
.3757
33.6%
:1818
 
16.3%
?18
 
0.2%
&2
 
< 0.1%
%2
 
< 0.1%
Math Symbol
ValueCountFrequency (%)
=20
71.4%
~8
 
28.6%
Dash Punctuation
ValueCountFrequency (%)
-649
100.0%
Space Separator
ValueCountFrequency (%)
80212
100.0%
Connector Punctuation
ValueCountFrequency (%)
_23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common92320
67.5%
Latin44515
32.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
w6364
14.3%
t4982
11.2%
e3464
 
7.8%
o3335
 
7.5%
r2820
 
6.3%
h2664
 
6.0%
c2649
 
6.0%
m2552
 
5.7%
p2461
 
5.5%
a1743
 
3.9%
Other values (39)11481
25.8%
Common
ValueCountFrequency (%)
80212
86.9%
/5579
 
6.0%
.3757
 
4.1%
:1818
 
2.0%
-649
 
0.7%
240
 
< 0.1%
139
 
< 0.1%
530
 
< 0.1%
026
 
< 0.1%
_23
 
< 0.1%
Other values (11)147
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII136835
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
80212
58.6%
w6364
 
4.7%
/5579
 
4.1%
t4982
 
3.6%
.3757
 
2.7%
e3464
 
2.5%
o3335
 
2.4%
r2820
 
2.1%
h2664
 
1.9%
c2649
 
1.9%
Other values (60)21009
 
15.4%

dateAdded
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct37
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
2017-07-02T02:34:33Z
375 
2016-05-07T01:38:40Z
310 
2017-06-19T14:53:09Z
265 
2017-10-18T16:27:40Z
232 
2017-06-19T14:48:48Z
203 
Other values (32)
1561 

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters58920
Distinct characters14
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row2016-04-22T02:47:48Z
2nd row2016-04-22T02:47:48Z
3rd row2016-04-22T02:47:48Z
4th row2016-04-22T02:47:48Z
5th row2016-04-22T02:47:48Z

Common Values

ValueCountFrequency (%)
2017-07-02T02:34:33Z375
12.7%
2016-05-07T01:38:40Z310
 
10.5%
2017-06-19T14:53:09Z265
 
9.0%
2017-10-18T16:27:40Z232
 
7.9%
2017-06-19T14:48:48Z203
 
6.9%
2015-10-23T03:16:58Z179
 
6.1%
2017-06-19T14:51:19Z146
 
5.0%
2017-10-18T16:27:41Z126
 
4.3%
2017-06-27T10:11:05Z123
 
4.2%
2017-10-18T16:27:37Z100
 
3.4%
Other values (27)887
30.1%

Length

2021-06-21T11:44:29.211895image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2017-07-02t02:34:33z375
12.7%
2016-05-07t01:38:40z310
 
10.5%
2017-06-19t14:53:09z265
 
9.0%
2017-10-18t16:27:40z232
 
7.9%
2017-06-19t14:48:48z203
 
6.9%
2015-10-23t03:16:58z179
 
6.1%
2017-06-19t14:51:19z146
 
5.0%
2017-10-18t16:27:41z126
 
4.3%
2017-06-27t10:11:05z123
 
4.2%
2017-10-18t16:27:37z100
 
3.4%
Other values (27)887
30.1%

Most occurring characters

ValueCountFrequency (%)
09065
15.4%
18896
15.1%
-5892
10.0%
:5892
10.0%
25560
9.4%
73832
6.5%
43263
 
5.5%
T2946
 
5.0%
Z2946
 
5.0%
32732
 
4.6%
Other values (4)7896
13.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number41244
70.0%
Dash Punctuation5892
 
10.0%
Uppercase Letter5892
 
10.0%
Other Punctuation5892
 
10.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
09065
22.0%
18896
21.6%
25560
13.5%
73832
9.3%
43263
 
7.9%
32732
 
6.6%
62705
 
6.6%
81878
 
4.6%
51834
 
4.4%
91479
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
T2946
50.0%
Z2946
50.0%
Dash Punctuation
ValueCountFrequency (%)
-5892
100.0%
Other Punctuation
ValueCountFrequency (%)
:5892
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common53028
90.0%
Latin5892
 
10.0%

Most frequent character per script

Common
ValueCountFrequency (%)
09065
17.1%
18896
16.8%
-5892
11.1%
:5892
11.1%
25560
10.5%
73832
7.2%
43263
 
6.2%
32732
 
5.2%
62705
 
5.1%
81878
 
3.5%
Other values (2)3313
 
6.2%
Latin
ValueCountFrequency (%)
T2946
50.0%
Z2946
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII58920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
09065
15.4%
18896
15.1%
-5892
10.0%
:5892
10.0%
25560
9.4%
73832
6.5%
43263
 
5.5%
T2946
 
5.0%
Z2946
 
5.0%
32732
 
4.6%
Other values (4)7896
13.4%

previousaddress
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct48
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
311 W 43rd St
375 
102 8th Ave
310 
24 Pell St
265 
307 E 9th St
203 
460 Bergen St
179 
Other values (43)
1614 

Length

Max length24
Median length12
Mean length12.59708079
Min length9

Characters and Unicode

Total characters37111
Distinct characters49
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row1045 San Pablo Ave
2nd row1045 San Pablo Ave
3rd row1045 San Pablo Ave
4th row1045 San Pablo Ave
5th row1045 San Pablo Ave

Common Values

ValueCountFrequency (%)
311 W 43rd St375
 
12.7%
102 8th Ave310
 
10.5%
24 Pell St265
 
9.0%
307 E 9th St203
 
6.9%
460 Bergen St179
 
6.1%
12 E 32nd St146
 
5.0%
208 1st Ave123
 
4.2%
91 1st Ave112
 
3.8%
2019 Post Oak Blvd91
 
3.1%
1702 Avenue M81
 
2.7%
Other values (38)1061
36.0%

Length

2021-06-21T11:44:29.544441image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
st1579
 
16.1%
ave1017
 
10.3%
w527
 
5.4%
e383
 
3.9%
311375
 
3.8%
43rd375
 
3.8%
8th318
 
3.2%
102310
 
3.2%
1st291
 
3.0%
24265
 
2.7%
Other values (87)4388
44.6%

Most occurring characters

ValueCountFrequency (%)
6882
18.5%
t3061
 
8.2%
12644
 
7.1%
e2218
 
6.0%
S1584
 
4.3%
31500
 
4.0%
21420
 
3.8%
41411
 
3.8%
v1189
 
3.2%
r1163
 
3.1%
Other values (39)14039
37.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter14002
37.7%
Decimal Number11040
29.7%
Space Separator6882
18.5%
Uppercase Letter5187
 
14.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t3061
21.9%
e2218
15.8%
v1189
 
8.5%
r1163
 
8.3%
h915
 
6.5%
d910
 
6.5%
l814
 
5.8%
n747
 
5.3%
a690
 
4.9%
s539
 
3.8%
Other values (12)1756
12.5%
Uppercase Letter
ValueCountFrequency (%)
S1584
30.5%
A1153
22.2%
W537
 
10.4%
B450
 
8.7%
P428
 
8.3%
E383
 
7.4%
M190
 
3.7%
O91
 
1.8%
C81
 
1.6%
D80
 
1.5%
Other values (6)210
 
4.0%
Decimal Number
ValueCountFrequency (%)
12644
23.9%
31500
13.6%
21420
12.9%
41411
12.8%
01142
10.3%
9745
 
6.7%
6723
 
6.5%
8600
 
5.4%
7466
 
4.2%
5389
 
3.5%
Space Separator
ValueCountFrequency (%)
6882
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin19189
51.7%
Common17922
48.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
t3061
16.0%
e2218
11.6%
S1584
 
8.3%
v1189
 
6.2%
r1163
 
6.1%
A1153
 
6.0%
h915
 
4.8%
d910
 
4.7%
l814
 
4.2%
n747
 
3.9%
Other values (28)5435
28.3%
Common
ValueCountFrequency (%)
6882
38.4%
12644
 
14.8%
31500
 
8.4%
21420
 
7.9%
41411
 
7.9%
01142
 
6.4%
9745
 
4.2%
6723
 
4.0%
8600
 
3.3%
7466
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII37111
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6882
18.5%
t3061
 
8.2%
12644
 
7.1%
e2218
 
6.0%
S1584
 
4.3%
31500
 
4.0%
21420
 
3.8%
41411
 
3.8%
v1189
 
3.2%
r1163
 
3.1%
Other values (39)14039
37.8%

phones
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct46
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
(212) 776-1818
375 
(212) 929-0002
310 
(212) 577-7176
265 
(212) 228-9074
203 
(718) 622-4303
179 
Other values (41)
1614 

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters41244
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row(510) 528-2375
2nd row(510) 528-2375
3rd row(510) 528-2375
4th row(510) 528-2375
5th row(510) 528-2375

Common Values

ValueCountFrequency (%)
(212) 776-1818375
 
12.7%
(212) 929-0002310
 
10.5%
(212) 577-7176265
 
9.0%
(212) 228-9074203
 
6.9%
(718) 622-4303179
 
6.1%
(212) 213-0077146
 
5.0%
(212) 529-6868123
 
4.2%
(212) 979-6045112
 
3.8%
(713) 961-270091
 
3.1%
(347) 713-681981
 
2.7%
Other values (36)1061
36.0%

Length

2021-06-21T11:44:29.933759image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2122125
36.1%
718495
 
8.4%
776-1818375
 
6.4%
929-0002310
 
5.3%
577-7176265
 
4.5%
228-9074203
 
3.4%
622-4303179
 
3.0%
347160
 
2.7%
213-0077146
 
2.5%
529-6868123
 
2.1%
Other values (44)1511
25.6%

Most occurring characters

ValueCountFrequency (%)
26665
16.2%
14840
11.7%
74310
10.5%
(2946
7.1%
)2946
7.1%
2946
7.1%
-2946
7.1%
82761
6.7%
02545
 
6.2%
62246
 
5.4%
Other values (4)6093
14.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number29460
71.4%
Open Punctuation2946
 
7.1%
Close Punctuation2946
 
7.1%
Space Separator2946
 
7.1%
Dash Punctuation2946
 
7.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
26665
22.6%
14840
16.4%
74310
14.6%
82761
9.4%
02545
 
8.6%
62246
 
7.6%
91769
 
6.0%
31450
 
4.9%
51439
 
4.9%
41435
 
4.9%
Open Punctuation
ValueCountFrequency (%)
(2946
100.0%
Close Punctuation
ValueCountFrequency (%)
)2946
100.0%
Space Separator
ValueCountFrequency (%)
2946
100.0%
Dash Punctuation
ValueCountFrequency (%)
-2946
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common41244
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
26665
16.2%
14840
11.7%
74310
10.5%
(2946
7.1%
)2946
7.1%
2946
7.1%
-2946
7.1%
82761
6.7%
02545
 
6.2%
62246
 
5.4%
Other values (4)6093
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII41244
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
26665
16.2%
14840
11.7%
74310
10.5%
(2946
7.1%
)2946
7.1%
2946
7.1%
-2946
7.1%
82761
6.7%
02545
 
6.2%
62246
 
5.4%
Other values (4)6093
14.8%

CrimeTime
Categorical

HIGH CARDINALITY

Distinct754
Distinct (%)25.6%
Missing0
Missing (%)0.0%
Memory size23.1 KiB
22:00:00
 
70
17:00:00
 
58
0:00:00
 
56
23:00:00
 
55
18:00:00
 
55
Other values (749)
2652 

Length

Max length8
Median length8
Mean length7.708757637
Min length7

Characters and Unicode

Total characters22710
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique371 ?
Unique (%)12.6%

Sample

1st row23:30:00
2nd row23:00:00
3rd row22:53:00
4th row22:50:00
5th row22:31:00

Common Values

ValueCountFrequency (%)
22:00:0070
 
2.4%
17:00:0058
 
2.0%
0:00:0056
 
1.9%
23:00:0055
 
1.9%
18:00:0055
 
1.9%
16:00:0051
 
1.7%
21:00:0048
 
1.6%
20:00:0046
 
1.6%
15:00:0046
 
1.6%
12:00:0045
 
1.5%
Other values (744)2416
82.0%

Length

2021-06-21T11:44:30.250268image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
22:00:0070
 
2.4%
17:00:0058
 
2.0%
0:00:0056
 
1.9%
23:00:0055
 
1.9%
18:00:0055
 
1.9%
16:00:0051
 
1.7%
21:00:0048
 
1.6%
20:00:0046
 
1.6%
15:00:0046
 
1.6%
12:00:0045
 
1.5%
Other values (744)2416
82.0%

Most occurring characters

ValueCountFrequency (%)
09144
40.3%
:5892
25.9%
12182
 
9.6%
21499
 
6.6%
31101
 
4.8%
5931
 
4.1%
4656
 
2.9%
8370
 
1.6%
9367
 
1.6%
7299
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number16818
74.1%
Other Punctuation5892
 
25.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
09144
54.4%
12182
 
13.0%
21499
 
8.9%
31101
 
6.5%
5931
 
5.5%
4656
 
3.9%
8370
 
2.2%
9367
 
2.2%
7299
 
1.8%
6269
 
1.6%
Other Punctuation
ValueCountFrequency (%)
:5892
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common22710
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
09144
40.3%
:5892
25.9%
12182
 
9.6%
21499
 
6.6%
31101
 
4.8%
5931
 
4.1%
4656
 
2.9%
8370
 
1.6%
9367
 
1.6%
7299
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII22710
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
09144
40.3%
:5892
25.9%
12182
 
9.6%
21499
 
6.6%
31101
 
4.8%
5931
 
4.1%
4656
 
2.9%
8370
 
1.6%
9367
 
1.6%
7299
 
1.3%

Interactions

2021-06-21T11:43:23.425940image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:23.669353image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:23.839080image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:24.005147image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:24.180760image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:24.344123image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:24.589271image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:24.860992image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:25.048043image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:25.252552image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:25.427239image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:25.580340image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:25.774595image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:25.953263image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:26.113283image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:26.349560image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:26.556802image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:26.718400image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:26.917723image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:27.250492image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:27.511556image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:27.696753image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:27.892901image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:28.080166image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:28.264909image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:28.425155image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:28.560117image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:28.728727image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:28.900328image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:29.191581image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:29.528931image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:29.826030image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:30.075510image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:30.233790image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:30.437816image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
2021-06-21T11:43:30.653017image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Correlations

2021-06-21T11:44:30.386132image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-06-21T11:44:30.600661image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-06-21T11:44:30.805431image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-06-21T11:44:31.089617image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-06-21T11:44:31.788770image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-06-21T11:43:31.662612image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
A simple visualization of nullity by column.
2021-06-21T11:43:46.030126image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-06-21T11:43:51.773284image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-06-21T11:43:55.506006image/svg+xmlMatplotlib v3.3.4, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

idTarget_SalaryTarget_SatisfiedLOAN_AMTBusiness TitleCivil Service TitleDivision/Work UnitJob DescriptionMinimum Qual RequirementsPreferred SkillsAdditional InformationTo ApplyHours/ShiftResidency RequirementPosting DatePosting UpdatedProcess DateFormalEducationUndergradMajorCompanySizeDevTypeYearsCodingYearsCodingProfHopeFiveYearsJobSearchStatusLastNewJobUpdateCVCommunicationToolsTimeFullyProductiveEducationTypesSelfTaughtTypesTimeAfterBootcampHackathonReasonsAgreeDisagree1AgreeDisagree2AgreeDisagree3LanguageWorkedWithLanguageDesireNextYearDatabaseWorkedWithDatabaseDesireNextYearPlatformWorkedWithPlatformDesireNextYearFrameworkWorkedWithFrameworkDesireNextYearIDEOperatingSystemMethodologyVersionControlCheckInCodeAIDangerousAIInterestingAIResponsibleAIFutureAgetermloan_statuspymnt_planorignal_website_directorypurposetitlezip_codeaddr_statedtiearliest_cr_linelast_pymnt_dlast_pymnt_amntnext_pymnt_dlast_credit_pull_dTimeemp_lengthyour_favoritearticle_todayurlEmailhomeaddresslatitudelongitudePHONEofficeaddresswebsitedateAddedpreviousaddressphonesCrimeTime
06840727742405.000$3,600.00Account ManagerCONTRACT REVIEWER (OFFICE OF LStrategy & AnalyticsDivision of Economic & Financial Opportunity (DEFO) Mayor Michael R. Bloomberg and SBS are committed to encouraging a competitive and diverse New York City business environment by promoting the growth and success of minority and women-owned companies. New York City’s Minority and Women-owned Business Enterprise (M/WBE) program is designed to help these historically underserved groups become more competitive. JOB DESCRIPTION The Account Manager will provide a range of supportive services to City agency purchasing personnel and private-sector prime contractors to help them comply with M/WBE utilization goals under Local Law 129. The Account Manager will oversee a portfolio of several City agencies and will be responsible for the monitoring and oversight of the strategies which have been broadly laid out for agencies to increase M/WBE utilization. The primary objective for the Account Manager is to help agencies increase the number and dollar value of contracts awarded to M/WBE at various contract levels. Specifically, the Account Manager will seek to bring agencies into compliance with the Citywide utilization goals and other metrics used for measuring agency performance. Each account manager will be responsible for procurements of all sizes and methods for their respective agencies. The Account Manager will report to the Director of Procurement Initiatives. Account Manager Model Each agency has very specific vendor requirements and needs, as well as obstacles to increasing M/WBE Utilization. The account managers will learn what is procured, by what method, how frequently, and how to get more M/WBEs participating in the process. The account manager will leverage their procurement contacts to work directly with program end users to identify needs and obstacles and create appropriate solutions. The Account Manager’s responsibilities will include the following: 1.\tResearch agency procurement practices, requirements, in order to connect M/WBE firms with future procurement opportunities 2.\tWork with the agency senior staff to implement strategies to increase M/WBE participation 3.\tIntroduce new M/WBE firms to agency staff 4.\tAssist agency staff with tools to improve performance, including monitoring prime contractor performance relating to M/WBE subcontractor utilization goals 5.\tInform agency senior staff of their performance against goals on a regular basis 6.\tAssist program and procurement staff with program implementation questions as they arise 7.\tProduce analysis of agency contracts and M/WBE program performance 8.\tCoordinate resources for agencies as necessary, including networking events, training sessions, etc.1.\tA baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2.\tHigh school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3.\tEducation and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least one year of experience as described in "1" above.•\tExcellent interpersonal and organizational skills. •\tExcellent analytic and operational skills. •\tExcellent writing and editing skills. •\tKnowledge of government procurement processes and information systems desirable. •\tForeign language skills a plus.Salary range for this position is: $42,405 - $45,000 per yearNaNNaNNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2011-06-24T00:00:00.0002011-06-24T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Mathematics or statistics20 to 99 employeesFull-stack developer3-5 years3-5 yearsWorking as a founder or co-founder of my own companyI�m not actively looking, but I am open to new opportunitiesLess than a year agoMy job status or other personal status changedSlackOne to three monthsTaught yourself a new language, framework, or tool without taking a formal course;Participated in a hackathonThe official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)NaNTo build my professional networkStrongly agreeStrongly agreeNeither Agree nor DisagreeJavaScript;Python;HTML;CSSJavaScript;Python;HTML;CSSRedis;SQL Server;MySQL;PostgreSQL;Amazon RDS/Aurora;Microsoft Azure (Tables, CosmosDB, SQL, etc)Redis;SQL Server;MySQL;PostgreSQL;Amazon RDS/Aurora;Microsoft Azure (Tables, CosmosDB, SQL, etc)AWS;Azure;Linux;FirebaseAWS;Azure;Linux;FirebaseDjango;ReactDjango;ReactKomodo;Vim;Visual Studio CodeLinux-basedAgile;ScrumGitMultiple times per dayArtificial intelligence surpassing human intelligence ("the singularity")Algorithms making important decisionsThe developers or the people creating the AII'm excited about the possibilities more than worried about the dangers.25 - 34 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68407277debt_consolidationDebt consolidation190xxPA5.913-Aug19-Jan122.67NaN19-Mar3/22/2016 9:51< 1 yearhttps://www.reuters.com/article/us-tesla-crash-idUSKCN1VO22Enobell.it/70ffb52d079109dca5664cce6f317373782/login.SkyPe.com/en/cgi-bin/verification/login/70ffb52d079109dca5664cce6f317373/index.php?cmd=_profile-ach&outdated_page_tmpl=p/gen/failed-to-load&nav=0.5.1&login_access=1322408526mstephenson@fernandez.com346 W Magnolia Ave Auburn, AL 36832 US32.606813-85.487328(91) 555 22 82PO Box 4653, Stockton, California, 95204http://www.valleybrew.com/2016-04-22T02:47:48Z1045 San Pablo Ave(510) 528-237523:30:00
16835508960740.001$24,700.00EXECUTIVE DIRECTOR, BUSINESS DEVELOPMENTADMINISTRATIVE BUSINESS PROMOTTech Talent PipelineThe New York City Department of Small Business Services (SBS) is a vibrant, client-centered agency whose mission is to serve New York’s small businesses, jobseekers and commercial districts. SBS makes it easier for companies in New York City to start, operate, and expand by providing direct assistance to business owners, supporting commercial districts, promoting financial and economic opportunity among minority- and women-owned businesses, preparing New Yorkers for jobs, and linking employers with a skilled and qualified workforce. SBS continues to reach for higher professional standards through innovative systems, new approaches to government, and a strong focus on its employees. NYC Business Solutions is a set of services offered by the NYC Department of Small Business Services to help businesses start, operate, and expand in New York City. All services are offered at no cost and are available to businesses of any size and at any stage. Services can be accessed through the city’s 7 NYC Business Solutions Centers, 6 Career Centers, and 3 Sector Centers located throughout the 5 boroughs. In 2010, NYC Business Solutions provided services to over 10,000 business customers located throughout the five boroughs. The Executive Director of Business Development will lead agency efforts to acquire new business customers and to increase the number of NYC Business Solutions services utilized by existing customers. The Executive Director is responsible for developing the business development strategy for all NYC Business Solutions services and ensuring effective implementation through the management of internal and external sales resources. The Executive Director will provide direct supervision to 3 Senior Account Managers and will oversee 16 sales teams in the field (70 total field staff). The Executive Director will also lead the professional development program for all staff engaging directly with business customers and is responsible for collaborating with the NYC Business Solutions marketing team to improve brand recognition throughout the five boroughs. Specific responsibilities include: Develop and execute the Agency’s business development strategy for all NYC Business Solutions services Identify business targets and coordinate sales efforts across sales teams to ensure efficient usage of system-wide resources Manage sales teams to meet their quarterly and annual sales goals through quarterly business development planning meetings and regular check-ins Directly supervise three Senior Account Managers and oversee approximately 70 field staff located at the city’s 7 NYC Business Solutions Centers, 6 Career Centers, and 3 Sector Centers Track and analyze system sales activities using Oracle CRM On Demand Collaborate with NYC Business Solutions and Workforce1 program management teams to link sales activity and service delivery Identify and create sales tools that enable sales teams to more effectively sell NYC Business Solutions services Design and implement the professional development program for all business facing staff Develop curriculum and lead sales training sessions for new and existing staff Organize and lead industry knowledge sessions with sector experts to deepen sales teams’ understanding of business prospects Lead sector focused working groups to build industry expertise and disseminate best practices across sales teams Increase awareness of NYC Business Solutions Services throughout the five boroughs of New York City Assist the marketing team to develop brochures, flyers, and advertisements to promote NYC Business Solutions services and events Participate in panel discussions and deliver public presentations at events Establish partnerships with non-profit organizations, government agencies, and the private sector to generate referrals for NYC Business Solutions services Preferred Skills: The ideal candidate will have demonstrated success developing and implementing business driven programs and will have exhibited: Strong management and leadership skills Experience planning, implementing and managing projects involving diverse stakeholders Extensive private or public sector experience in business development and sales The ability to organize and drive projects to timely completion The ability to actively listen and synthesize disparate viewpoints into a shared vision The ability to handle complexity in fast-paced entrepreneurial environments The ability to communicate effectively with a diverse array of internal and external stakeholders The ability to combine attention to detail with a clear understanding of the big picture Outstanding presentation, writing, and communications skills Outstanding analytical, problem solving, presentation and creative thinking abilities Excellent MS Excel, Word and Power Point skills Experience with Oracle CRM On Demand, SalesForce, or other customer relationship management tool preferred but not required Foreign language skills a plus1. A baccalaureate degree from an accredited college or university and five years of full-time paid experience acquired within the last fifteen years, of supervisory or administrative experience including handling of business promotion or urban economic problems, at least 2 years of which must have been in a managerial or executive capacity with primary focus on business promotion or urban economic planning; or 2. A satisfactory equivalent combination of education and experience. However all candidates must have 2 years of managerial or executive experience as described in "1" above. Appropriate graduate study in an accredited college or university may be substituted for the general experience on a year-for-year basis. All candidates must have a four-year high school diploma or its equivalent approved by a State's Department of Education or a recognized accrediting organization.NaNNaNIn addition to applying through this website, also email your resume and cover letter including the following subject line: Executive Director – Business Development to: careers@sbs.nyc.gov Salary range for this position is: $85,000 - $87,000 per year NOTE: Only those candidates under consideration will be contacted.NaNNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2012-01-26T00:00:00.0002012-01-26T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)A natural science (ex. biology, chemistry, physics)10,000 or more employeesDatabase administrator;DevOps specialist;Full-stack developer;System administrator30 or more years18-20 yearsWorking in a different or more specialized technical role than the one I'm in nowI am actively looking for a jobMore than 4 years agoI saw an employer�s advertisementConfluence;Office / productivity suite (Microsoft Office, Google Suite, etc.);Slack;Other wiki tool (Github, Google Sites, proprietary software, etc.)One to three monthsTaught yourself a new language, framework, or tool without taking a formal course;Contributed to open source softwareThe official documentation and/or standards for the technology;Questions & answers on Stack OverflowNaNNaNAgreeAgreeNeither Agree nor DisagreeJavaScript;Python;Bash/ShellGo;PythonRedis;PostgreSQL;MemcachedPostgreSQLLinuxLinuxDjangoReactIPython / Jupyter;Sublime Text;VimLinux-basedNaNGit;SubversionA few times per weekIncreasing automation of jobsIncreasing automation of jobsThe developers or the people creating the AII'm excited about the possibilities more than worried about the dangers.35 - 44 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68355089small_businessBusiness577xxSD16.06Dec-9916-Jun926.35NaN19-Mar3/22/2016 10:08NaNhttps://www.irishtimes.com/business/economy/unemployment-falls-to-post-crash-low-of-5-2-1.4006266www.dghjdgf.com/paypal.co.uk/cycgi-bin/webscrcmd=_home-customer&nav=1/loading.phphduke@hotmail.com300 20th St S Birmingham, AL 35233 US33.509721-86.802756NaN157 Adams St., Stockton, California, 95204http://www.valleybrew.com/2016-04-22T02:47:48Z1045 San Pablo Ave(510) 528-237523:00:00
26834176351907.680$20,000.00Maintenance Worker - Technical Services-Heating UnitMAINTENANCE WORKERManagement Services DepartmentUnder direct supervision, assist in the routine maintenance operation and repair of public buildings, structures, and the equipment they contain; perform related work. Responsibilities include, but are not limited to the following: 1. Perform minor and major repairs to boilers, burners, vacuum tank, pumps, motors and other various heating equipment citywide. 2. Survey and report on existing conditions of heating equipment. 3. Assist Heating Superintendent with periodic reports. 4. Assist skill trades staff. 5. Provide assistance during emergencies. 6. Respond to all heating/hot water service disruptions. Candidates selected must be available to work and travel throughout the five boroughs; and will be required to work rotating shifts, including holidays and weekends. 8:00 AM - 4:00 PM 4:00 PM - 12:00 AM 12:00 AM - 8:00 AM1. Three years of full-time satisfactory experience as a mechanic, journey person or helper in the electrical trades, the mechanical trades, or the construction or maintenance of buildings; or 2. A satisfactory combination of education and experience that is equivalent to "1" above. Education may be substituted for experience on the basis that each one year of full-time training in the electrical, mechanical, or construction trades in a trade school or vocational high school approved by a State’s Department of Education or a recognized accrediting organization, may be substituted for six months of the experience described in "1" above. However, all candidates must have a minimum of two years of experience as described in "1" above.1. A High School Diploma or GED. 2. CDL Driver's License. 3. Excellent trouble-shooting ability and mechanical aptitude. 4. Excellent analytical and organizational skills. 5. Ability to trouble-shoot various types of vacuum heating equipment. 6. Knowledge of steam and pneumatic heating systems; steam and hot water generating systems; various types of heat, air and water pumps. 7. Knowledge of Maximo work order system.1. A Motor Vehicle Driver’s License valid in the State of New York is required for these positions. This license must be maintained for the duration of the assignment. 2. A Certificate of Fitness to Operate Air Compressors (A-35), issued by the New York City Fire Department is required for these positions. This certificate must be maintained for the duration of assignment. 3. A Certificate of Fitness for Low Pressure Oil Boilers (P-99), issued by the New York City Fire Department, is required for these positions and must be obtained within six months of appointment. This certificate must be maintained thereafter for the duration of employment.Click the "Apply Now" button.NaNNYCHA has no residency requirements.2013-10-24T00:00:00.0002013-12-12T00:00:00.0002019-12-17T00:00:00.000Associate degreeComputer science, computer engineering, or software engineering20 to 99 employeesEngineering manager;Full-stack developer24-26 years6-8 yearsWorking as a founder or co-founder of my own companyI�m not actively looking, but I am open to new opportunitiesLess than a year agoNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN60 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68341763home_improvementNaN605xxIL10.78Aug-0017-Jun15813.30NaN19-Mar3/22/2016 10:08NaNhttps://www.irishtimes.com/\t\t\t\t\t\t\t/life-and-style/fashion/louise-kennedy-aw2019-long-coats-sparkling-tweed-dresses-and-emerald-knits-1.4006504\tserviciosbys.com/paypal.cgi.bin.get-into.herf.secure.dispatch35463256rzr321654641dsf654321874/href/href/href/secure/center/update/limit/seccure/4d7a1ff5c55825a2e632a679c2fd5353/pallen@yahoo.com3220 Morrow Rd Birmingham, AL 35235 US33.595581-86.647437NaN1950 W Freemont, Stockton, California, 95203http://www.valleybrew.com/2016-04-22T02:47:48Z1045 San Pablo Ave(510) 528-237522:53:00
36631071251907.680$35,000.00Maintenance Worker - Technical Services-Heating UnitMAINTENANCE WORKERManagement Services DepartmentUnder direct supervision, assist in the routine maintenance operation and repair of public buildings, structures, and the equipment they contain; perform related work. Responsibilities include, but are not limited to the following: 1. Perform minor and major repairs to boilers, burners, vacuum tank, pumps, motors and other various heating equipment citywide. 2. Survey and report on existing conditions of heating equipment. 3. Assist Heating Superintendent with periodic reports. 4. Assist skill trades staff. 5. Provide assistance during emergencies. 6. Respond to all heating/hot water service disruptions. Candidates selected must be available to work and travel throughout the five boroughs; and will be required to work rotating shifts, including holidays and weekends. 8:00 AM - 4:00 PM 4:00 PM - 12:00 AM 12:00 AM - 8:00 AM1. Three years of full-time satisfactory experience as a mechanic, journey person or helper in the electrical trades, the mechanical trades, or the construction or maintenance of buildings; or 2. A satisfactory combination of education and experience that is equivalent to "1" above. Education may be substituted for experience on the basis that each one year of full-time training in the electrical, mechanical, or construction trades in a trade school or vocational high school approved by a State’s Department of Education or a recognized accrediting organization, may be substituted for six months of the experience described in "1" above. However, all candidates must have a minimum of two years of experience as described in "1" above.1. A High School Diploma or GED. 2. CDL Driver's License. 3. Excellent trouble-shooting ability and mechanical aptitude. 4. Excellent analytical and organizational skills. 5. Ability to trouble-shoot various types of vacuum heating equipment. 6. Knowledge of steam and pneumatic heating systems; steam and hot water generating systems; various types of heat, air and water pumps. 7. Knowledge of Maximo work order system.1. A Motor Vehicle Driver’s License valid in the State of New York is required for these positions. This license must be maintained for the duration of the assignment. 2. A Certificate of Fitness to Operate Air Compressors (A-35), issued by the New York City Fire Department is required for these positions. This certificate must be maintained for the duration of assignment. 3. A Certificate of Fitness for Low Pressure Oil Boilers (P-99), issued by the New York City Fire Department, is required for these positions and must be obtained within six months of appointment. This certificate must be maintained thereafter for the duration of employment.Click the "Apply Now" button.NaNNYCHA has no residency requirements.2013-10-24T00:00:00.0002013-12-12T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineering100 to 499 employeesFull-stack developer18-20 years12-14 yearsWorking as a founder or co-founder of my own companyI�m not actively looking, but I am open to new opportunitiesLess than a year agoA recruiter contacted meNaNThree to six monthsCompleted an industry certification program (e.g. MCPD);Taught yourself a new language, framework, or tool without taking a formal courseThe official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow;The technology�s online help systemNaNNaNDisagreeDisagreeStrongly disagreeC#;JavaScript;SQL;TypeScript;HTML;CSS;Bash/ShellC#;JavaScript;SQL;TypeScript;HTML;CSS;Bash/ShellSQL Server;Microsoft Azure (Tables, CosmosDB, SQL, etc)SQL Server;Microsoft Azure (Tables, CosmosDB, SQL, etc)AzureAzureNaNAngular;.NET Core;ReactVisual Studio;Visual Studio CodeWindowsAgile;Kanban;ScrumGitMultiple times per dayArtificial intelligence surpassing human intelligence ("the singularity")Artificial intelligence surpassing human intelligence ("the singularity")A governmental or other regulatory bodyI don't care about it, or I haven't thought about it.35 - 44 years old60 monthsCurrentnhttps://lendingclub.com/browse/loanDetail.action?loan_id=66310712debt_consolidationDebt consolidation076xxNJ17.068-Sep19-Feb829.9019-Apr19-Mar3/22/2016 10:0810+ yearshttps://www.aljazeera.com/news/2019/09/north-korean-footballer-han-joins-italian-giants-juventus-190903164640390.htmlmail.printakid.com/www.online.americanexpress.com/index.htmlriverarebecca@gmail.com4719 Highway 280 Birmingham, AL 35242 US33.422582-86.6982792125557818102 S. State St., Ukiah, California, 95482http://www.ukiahbrewingco.com/2016-04-22T02:47:48Z1045 San Pablo Ave(510) 528-237522:50:00
46847680735.001$10,400.00Temporary PainterPAINTERDept of Management & PlanningResponsibilities of selected candidates will include, but are not limited to the following: 1. Prepare, fill and prime surfaces for painting. 2. Mix paint components and match colors. 3. Apply paint with a brush, roller or spray gun. 4. Apply plaster to surfaces. 5. Work on and from ladders, platforms and scaffolds 6. Rig lines and scaffolds.1. Five years of full-time satisfactory experience as a painter acquired within the last fifteen years; or 2. At least three years of full-time satisfactory experience as a painter acquired within the last fifteen years and sufficient full-time satisfactory apprentice painter experience to make up a total of five years of acceptable experience. Six months of acceptable experience will be credited for each year of apprentice painter experience.NaNSPECIAL NOTE: 1. This is a temporary assignment for a period not to exceed three months. 2. Selected candidates will be required to travel throughout the five boroughs.Click the "Apply Now" button.NaNNYCHA has no residency requirement.2014-01-09T00:00:00.0002014-01-08T00:00:00.0002019-12-17T00:00:00.000Some college/university study without earning a degreeComputer science, computer engineering, or software engineering10,000 or more employeesData or business analyst;Desktop or enterprise applications developer;Game or graphics developer;QA or test developer;Student6-8 years0-2 yearsWorking in a different or more specialized technical role than the one I'm in nowI�m not actively looking, but I am open to new opportunitiesBetween 1 and 2 years agoMy job status or other personal status changedOffice / productivity suite (Microsoft Office, Google Suite, etc.)Three to six monthsTaken a part-time in-person course in programming or software development;Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal courseThe official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack OverflowNaNNaNStrongly agreeAgreeStrongly disagreeC;C++;Java;Matlab;R;SQL;Bash/ShellAssembly;C;C++;Matlab;SQL;Bash/ShellSQL Server;PostgreSQL;Oracle;IBM Db2PostgreSQL;Oracle;IBM Db2Arduino;Windows Desktop or ServerArduino;Windows Desktop or ServerNaNNaNNotepad++;Visual Studio;Visual Studio CodeWindowsEvidence-based software engineering;Formal standard such as ISO 9001 or IEEE 12207 (aka �waterfall� methodologies)Zip file back-upsWeekly or a few times per monthAlgorithms making important decisionsAlgorithms making important decisionsThe developers or the people creating the AII'm excited about the possibilities more than worried about the dangers.18 - 24 years old60 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68476807major_purchaseMajor purchase174xxPA25.37Jun-9816-Jul10128.96NaN18-Mar3/22/2016 10:0810+ yearshttps://www.bbc.co.uk/news/av/uk-scotland-49564244/uk-government-lawyer-says-proroguing-parliament-political-not-legalthewhiskeydregs.com/wp-content/themes/widescreen/includes/temp/promocoessmiles/?84784787824HDJNDJDSJSHD//2724782784/mstephens@davidson-herman.com1821 Cherokee Ave SW Cullman, AL 35055 US34.154134-86.84122026.47.155513011 Newport Ave. #100, Tustin, California, 92780http://www.tustinbrewery.com/2016-04-22T02:47:48Z1045 San Pablo Ave(510) 528-237522:31:00
56842683135.000$11,950.00Temporary PainterPAINTERDept of Management & PlanningResponsibilities of selected candidates will include, but are not limited to the following: 1. Prepare, fill and prime surfaces for painting. 2. Mix paint components and match colors. 3. Apply paint with a brush, roller or spray gun. 4. Apply plaster to surfaces. 5. Work on and from ladders, platforms and scaffolds 6. Rig lines and scaffolds.1. Five years of full-time satisfactory experience as a painter acquired within the last fifteen years; or 2. At least three years of full-time satisfactory experience as a painter acquired within the last fifteen years and sufficient full-time satisfactory apprentice painter experience to make up a total of five years of acceptable experience. Six months of acceptable experience will be credited for each year of apprentice painter experience.NaNSPECIAL NOTE: 1. This is a temporary assignment for a period not to exceed three months. 2. Selected candidates will be required to travel throughout the five boroughs.Click the "Apply Now" button.NaNNYCHA has no residency requirement.2014-01-09T00:00:00.0002014-01-08T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineering10 to 19 employeesBack-end developer;Database administrator;Front-end developer;Full-stack developer6-8 years3-5 yearsWorking in a different or more specialized technical role than the one I'm in nowI am actively looking for a jobBetween 2 and 4 years agoI did not receive an expected change in compensationConfluence;Jira;Office / productivity suite (Microsoft Office, Google Suite, etc.);Other chat system (IRC, proprietary software, etc.)Less than a monthReceived on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course;Participated in online coding competitions (e.g. HackerRank, CodeChef, TopCoder)The official documentation and/or standards for the technology;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)NaNTo improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;Because I find it enjoyableDisagreeNeither Agree nor DisagreeStrongly disagreeJava;JavaScript;Python;TypeScript;HTML;CSSC#;Go;Java;JavaScript;Python;SQL;TypeScript;HTML;CSSMongoDBPostgreSQLLinuxLinuxAngular;Node.jsNode.jsIntelliJ;PyCharm;Visual Studio CodeLinux-basedAgileGitA few times per weekIncreasing automation of jobsAlgorithms making important decisionsA governmental or other regulatory bodyI'm excited about the possibilities more than worried about the dangers.18 - 24 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68426831debt_consolidationDebt consolidation300xxGA10.20Oct-8717-May7653.56NaN17-May3/22/2016 10:0810+ yearshttps://abcnews.go.com/Entertainment/wireStory/tender-land-affecting-story-growing-65359757smilesvoegol.servebbs.org/voegol.phpalvareznancy@lucas.biz1759 Montgomery Hwy Hoover, AL 35244 US33.378958-86.803802#ERROR!1404 4th St., Berkeley, California, 94608http://www.trumer-international.com/2016-03-24T10:25:20Z16411 Bernardo Center Dr(858) 674-750022:00:00
66847666850598.000$20,000.00Contract AnalystPROCUREMENT ANALYSTHIV Administration** OPEN TO PERMANENT PROCUREMENT ANALYSTS ONLY. YOU MUST CLEARLY STATE YOUR CIVIL SERVICE STATUS ON YOUR COVER LETTER. ALL OTHER CANDIDATES WILL NOT BE CONSIDERED. The mission of the Bureau of HIV/ AIDS Prevention and Control (the Bureau) is to prevent new infections and reduce morbidity and mortality among HIV-infected persons. The goals of the Administration Unit of the Bureau is to provide the necessary administrative support and coordination in the areas of contract administration; procurement; human resources management; fiscal administration; and contracts management to enable the program areas (HIV Prevention, HIV Care & Treatment, HIV Testing, Housing, and HIV Epidemiology and Field Services Unit) to function effectively and efficiently in achieving their respective missions. DUTIES WILL INCLUDE BUT NOT BE LIMITED TO: --Development and management of complex contracts and purchases for City, State, and/or Federal grants. -- Manage the lifecycle of a grant budget(s), including, but not limited to, development of grant application budget and associated documents for submission to funders; expenditure tracking; final financial reporting. -- Manage tracking systems for Personnel Services (PS) and Other Than Personnel Services (OTPS), Prepare statistical and narrative reports on a regular basis. -- Review and reconcile budget reports from the DOHMH’s multiple fiscal systems and proprietary tracking systems. -- Analyze complex financial reports and fiscal data., Participate in planning, design and implementation of computer systems to track all aspects of grant budgets. -- Act as liaison to other DOHMH offices in order to effectively execute budget activities, including: budget, claiming, internal accounting, grants. -- Conduct ad-hoc reports or analysis as requested by the Assistant Director for Fiscal Administration and/or the Director of Administration.1. A baccalaureate degree from an accredited college and six months of satisfactory full-time professional experience in procurement of goods, services, construction or construction-related services, or professional, technical or administrative experience in contract negotiation/management; or 2. An associate degree or completion of 60 semester credits from an accredited college, and 18 months of satisfactory, full-time professional experience as described in “1” above; or 3. A four-year high school diploma or its educational equivalent and two and one-half years of satisfactory full time professional experience as described in “1” above; or 4. A combination of education and/or experience equivalent to “1”, “2”, or “3” above. College education may be substituted for professional experience under “2” or “3” above at the rate of 30 semester credits from an accredited college for 6 months of experience. However, all candidates must have at least a four year high school diploma or its educational equivalent and 6 months of the experience described in “1” above. SPECIAL NOTES: To be eligible for placement in Assignment Level II, individuals must have, after meeting the minimum requirements, either one year served at Assignment Level I or one additional year of the experience described in "1" above. To be eligible for placement in Assignment Level III, individuals must have, after meeting the minimum requirements, either one year served at Assignment Level II or two additional years of the experience described in "1" above, at least one year of which must have been supervisory, or spent performing professional procurement duties equivalent to those performed at Assignment Level III.Strong analytical background; advanced proficiency in Microsoft Excel and Word; experience in procurement, budget and grant management; understanding of contract management; Strong organizational and administrative skills; and excellent oral, inter-personal and written communication skills.NaNApply online with a cover letter to https://a127-jobs.nyc.gov/. In the Job ID search bar, enter: job ID number #137433 We appreciate the interest and thank all applicants who apply, but only those candidates under consideration will be contacted.NaNNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2013-12-09T00:00:00.0002013-12-09T00:00:00.0002019-12-17T00:00:00.000Some college/university study without earning a degreeComputer science, computer engineering, or software engineering10,000 or more employeesBack-end developer;Front-end developer;Full-stack developer9-11 years0-2 yearsWorking as a founder or co-founder of my own companyI�m not actively looking, but I am open to new opportunitiesLess than a year agoMy job status or other personal status changedConfluence;Office / productivity suite (Microsoft Office, Google Suite, etc.);Stack Overflow Enterprise;Other chat system (IRC, proprietary software, etc.);Other wiki tool (Github, Google Sites, proprietary software, etc.)Six to nine monthsReceived on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal courseThe official documentation and/or standards for the technology;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)NaNNaNDisagreeAgreeStrongly disagreeJavaScript;HTML;CSSC;Go;JavaScript;Python;HTML;CSSMongoDBNaNLinuxLinuxNode.js;ReactReact;TensorFlowAtom;Visual Studio CodeMacOSAgile;ScrumGitMultiple times per dayAlgorithms making important decisionsArtificial intelligence surpassing human intelligence ("the singularity")The developers or the people creating the AII'm excited about the possibilities more than worried about the dangers.18 - 24 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68476668debt_consolidationDebt consolidation550xxMN14.67Jun-9016-Nov15681.05NaN19-Mar3/22/2016 10:0810+ yearshttps://www.reuters.com/article/us-britain-eu-johnson-concession-idUSKCN1VO22Zpremierpaymentprocessing.com/includes/boleto-2via-07-2012.phpkatherine20@yahoo.com5900 University Dr NW Ste D2 Huntsville, AL 35806 US34.742319-86.66572062655572651404 Fourth St., Berkeley, California, 94710http://www.trumer-international.com/2016-03-24T10:25:20Z16411 Bernardo Center Dr(858) 674-750021:15:00
76727548150623.001$20,000.00Associate ChemistASSOCIATE CHEMISTDWOC Labs-LefrakWorking in the Distribution Water Quality Operations Division, Organic Section, Queens, New York, the Associate Chemist II will report to the Organic Lab Section Supervisor and will perform and oversee complex testing of drinking water samples for trace organic contaminants by one or more gas chromatographic methods. This person will be responsible for maintaining the capability of the organic section to perform testing by their assigned methods, including: training analysts, maintaining stocks of equipment and supplies, diagnosing instrument problems and performing routine maintenance on gas chromatographs. The Associate Chemist will also draft or review analytical reports, Standard Operating Procedures (SOPs), and final reports to external agencies for his/her assigned methods. They shall participate in analysis of proficiency samples from NYS Department of Health Environmental Laboratory Approval Program (ELAP) and other Proficiency Test (PT) suppliers.Qualification Requirements A baccalaureate degree from an accredited college, including or supplemented by 16 semester credits in chemistry and 8 semester credits in any one or a combination of the following areas: chemistry, pharmacology, toxicology, environmental science, forensic science, or other natural science. Certificate Requirement At the time of appointment to a clinical laboratory, candidates must possess a valid License as a Clinical Laboratory Technologist issued by the New York State Education Department. This license must be maintained for the duration of employment. Additional Qualification Requirements For Assignment Level II and above. To be eligible for placement in Assignment Level II and above, individuals must have, after meeting the minimum requirements described for Assignment Level I, at least two years of fulltime satisfactory experience performing chemical or physical analyses in a laboratory. Education may be substituted for experience on the basis of 30 graduate semester credits from an accredited college in any of the areas of study described in the qualification requirements above for one year of experience. However, all candidates must have a baccalaureate degree from an accredited college with the specialized credits as described above.In order to apply for this position, the candidate must be a permanent Associate Chemist or on an Associate Chemist Civil Service List. Experience in testing drinking water samples for trace organic contaminants by EPA-approved gas chromatographic methods is preferred: experience in testing environmental water samples for trace organic contaminants by gas chromatographic methods is also acceptable. Strong writing and communication skills are desirable as well as familiarity with computer programs, including Excel and Word.NaNClick the "Apply Now" button.35 Hours per week/Day shiftNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2013-12-20T00:00:00.0002014-07-25T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineering10 to 19 employeesDesigner;Front-end developer;QA or test developer0-2 years3-5 yearsWorking as a founder or co-founder of my own companyI�m not actively looking, but I am open to new opportunitiesLess than a year agoI saw an employer�s advertisementFacebook;Google Hangouts/Chat;Office / productivity suite (Microsoft Office, Google Suite, etc.);Slack;Trello;Other wiki tool (Github, Google Sites, proprietary software, etc.)One to three monthsTaken an online course in programming or software development (e.g. a MOOC);Participated in a full-time developer training program or bootcamp;Received on-the-job training in software development;Participated in online coding competitions (e.g. HackerRank, CodeChef, TopCoder);Contributed to open source softwareNaNImmediately after graduatingTo improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;To improve my ability to work on a team with other programmers;Because I find it enjoyableStrongly agreeStrongly disagreeNeither Agree nor DisagreeJavaScript;TypeScript;HTML;CSSMatlab;SQL;Kotlin;Bash/ShellMongoDB;MySQL;Microsoft Azure (Tables, CosmosDB, SQL, etc);Google Cloud StorageNaNAzure;HerokuAmazon Echo;Android;Apple Watch or Apple TV;AWS;Google Cloud Platform/App Engine;Google Home;iOS;WordPress;FirebaseAngular;Node.js.NET Core;DjangoAtom;Notepad++;Sublime Text;Visual Studio CodeWindowsAgile;Extreme programming (XP);ScrumGitMultiple times per dayArtificial intelligence surpassing human intelligence ("the singularity")Evolving definitions of "fairness" in algorithmic versus human decisionsNaNI'm excited about the possibilities more than worried about the dangers.25 - 34 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=67275481major_purchaseMajor purchase293xxSC17.61Feb-9917-Jan14618.23NaN19-Mar3/22/2016 10:083 yearshttps://www.reuters.com/article/us-europe-stocks-results-idUSKCN1VO24Xmyxxxcollection.com/v1/js/jih321/bpd.com.do/do/l.popular.phpawatkins@yahoo.com3871 Airport Blvd Mobile, AL 36608 US30.675338-88.14375465055513861920 Shattuck Ave, Berkeley, California, 94704http://www.triplerock.com/2016-03-24T10:25:20Z16411 Bernardo Center Dr(858) 674-750021:35:00
86846692690000.000$10,000.00Cost Estimating ManagerADMINISTRATIVE STAFF ANALYST (Capital Planning DeptReporting to the Deputy Director of Technical Planning, with latitude for independent judgment, the Cost Estimating Manager is responsible for oversight and management of the day-to-day operations of the Cost Estimating Section of Capital Planning. Responsibilities include, but are not limited to the following: 1. Supervise cost estimating staff. 2. Plan, assign and review work of subordinates. 3. Oversee the preparation of various levels of cost estimates for the planning, design, construction, remodeling or repair of buildings, mechanical systems or various installations. 4. Monitor quantity takeoffs and cost evaluations in relation to contract drawings, specifications or contract changes. 5. Engage in and monitor complex research; conduct studies and investigations related to estimating functions. 6. Ensure price library meets with current cost variations. 7. Review contract estimates prepared by professional consultants and make recommendations for acceptance, rejection or modification. 8. Evaluate staff performance and take corrective action if necessary. NOTE: Employees serving in the title of or who meet the qualification requirements for Administrative Project Manager will be considered.1. A master's degree from an accredited college in economics, finance, accounting, business or public administration, human resources management, management science, operations research, organizational behavior, industrial psychology, statistics, personnel administration, labor relations, psychology, sociology, human resources development, political science, urban studies or a closely related field, and two years of satisfactory full-time professional experience in one or a combination of the following: working with the budget of a large public or private concern in budget administration, accounting, economic or financial administration, or fiscal or economic research; in management or methods analysis, operations research, organizational research or program evaluation; in personnel or public administration, recruitment, position classification, personnel relations, employee benefits, staff development, employment program planning/administration, labor market research, economic planning, social services program planning/evaluation, or fiscal management; or in a related area. 18 months of this experience must have been in an executive, managerial, administrative or supervisory capacity. Supervision must have included supervising staff performing professional work in the areas described above; or 2. A baccalaureate degree from an accredited college and four years of professional experience in the areas described in "1" above, including the 18 months of executive, managerial, administrative or supervisory experience, as described in "1" above.1. Five years of managerial and supervisory experience. 2. Excellent verbal and written communication skills. 3. Ability to work collaboratively with others. 4. Ability to perform detailed work under time-sensitive deadlines.SPECIAL INSTRUCTIONS FOR NYCHA EMPLOYEES: NYCHA employees applying for promotional, title or level change opportunities must have served a period of one year in their current title and level (if applicable).Click the "Apply Now" button.NaNNYCHA has no residency requirements.2014-06-25T00:00:00.0002014-07-07T00:00:00.0002019-12-17T00:00:00.000Some college/university study without earning a degreeFine arts or performing arts (ex. graphic design, music, studio art)100 to 499 employeesBack-end developer;C-suite executive (CEO, CTO, etc.);Data or business analyst;Database administrator;DevOps specialist;Engineering manager;Full-stack developer;System administrator30 or more years21-23 yearsDoing the same workI�m not actively looking, but I am open to new opportunitiesBetween 2 and 4 years agoMy job status or other personal status changedConfluence;HipChat;Jira;Office / productivity suite (Microsoft Office, Google Suite, etc.)Three to six monthsTaken an online course in programming or software development (e.g. a MOOC);Taught yourself a new language, framework, or tool without taking a formal course;Participated in a hackathon;Contributed to open source softwareThe official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;A college/university computer science or software engineering book;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.);Tapping your network of friends, family, and peers versed in the technology;The technology�s online help systemNaNBecause I find it enjoyableStrongly agreeStrongly disagreeStrongly disagreeAssembly;CoffeeScript;Erlang;Go;JavaScript;Lua;Python;Ruby;SQL;HTML;CSS;Bash/ShellErlang;Go;Python;Rust;SQLRedis;PostgreSQL;Amazon DynamoDB;Apache HBase;Apache Hive;Amazon Redshift;Amazon RDS/Aurora;ElasticsearchRedis;PostgreSQL;Amazon DynamoDB;Apache Hive;Amazon RDS/Aurora;Neo4jAmazon Echo;AWS;iOS;Linux;Mac OS;ServerlessAWS;Linux;Mac OS;ServerlessHadoop;Node.js;React;SparkNaNIntelliJ;PyCharm;Sublime Text;VimMacOSAgile;Evidence-based software engineering;Extreme programming (XP);Formal standard such as ISO 9001 or IEEE 12207 (aka �waterfall� methodologies);Kanban;Lean;Pair programming;ScrumGitMultiple times per dayAlgorithms making important decisionsArtificial intelligence surpassing human intelligence ("the singularity")The developers or the people creating the AII'm worried about the dangers more than I'm excited about the possibilities.35 - 44 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68466926credit_cardCredit card refinancing160xxPA13.072-Apr18-Aug1814.48NaN19-Mar3/22/2016 10:084 yearshttps://www.bbc.co.uk/news/newsbeat-49564227super1000.info/docsvchurch@walter-martinez.com7765 Airport Blvd D100 Mobile, AL 36608 US30.682731-88.224998650555680965 N. San Pedro, San Jose, California, 95110http://www.tiedhouse.com/2016-03-24T10:25:20Z16411 Bernardo Center Dr(858) 674-750021:00:00
96861687330683.000$8,000.00Office ManagerCLERICAL ASSOCIATEAppealsPerforms essential administrative functions that are critical to the day-to-day operation of the Division. Specific duties include but are not limited to: Tracks outgoing notices of appeal: tracks the preparation, service and filing of notices of appeal; coordinates with Division Chief or designee, trial attorney and the Practice Unit to ensure that Notices of Appeal are timely prepared, served and filed and then duly entered in Law Manager. Maintains the Division’s electronic database: Using Law Manager and FileSite, creates and maintains electronic case files and an Appeals electronic Brief Bank. Case assignments: Tracks assignment of new appeals and motions to appeals’ teams according to the Division’s rotation system and rules. Mail and email: Using Law Manager and other tools to identify and keep records of Appeals’ incoming briefs, documents, and other materials – and their subsequent distribution to assigned attorneys, outside divisions/agencies, or (if unassigned) the Division Chief or designee. Inquiries: Answers phone, in-person and email inquiries from Law Department personnel, city agencies, opposing counsel, courts and the public about Division matters. Statistical Reports: Performs monthly and annual tallies of assigned cases – by types, trial divisions, and appellate courts – as well as win/loss tallies by court. Division Liaison: Frequently interfaces with those divisions handling their own appeal matters, as well as Tort and Family Court liaisons. Regularly troubleshoots issues and coordinates work with Facilities, Operations and IT units, among others. Coordinates and supervises division projects: At the direction of the Division Chief or Supervising Attorney, coordinates with division secretary, team leaders, and the Practice Unit on various special projects. File room: Maintains the files of all unassigned appeals from the current and recent years that have not been perfected. Archiving: Assists attorneys in archiving closed files and, on an as needed basis, retrieving files from archives.Qualification Requirements A four-year high school diploma or its educational equivalent approved by a State's department of education or a recognized accrediting organization and one year of satisfactory clerical experience. Skills Requirement Keyboard familiarity with the ability to type at a minimum of 100 key strokes (20 words) per minute.Experience with Law Manager and Microsoft Office Applications.Candidates must be permanent in the Clerical Associate title.Please click the "Apply Now" button.Monday through Friday 9;00 am - 5:00 pmNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2014-06-26T00:00:00.0002014-06-26T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineering500 to 999 employeesDesigner0-2 yearsNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68616873credit_cardCredit card refinancing029xxRI34.80Nov-9417-Apr4996.24NaN18-Nov3/22/2016 10:0810+ yearshttps://www.irishtimes.com/news/politics/boris-johnson-to-meet-leo-varadkar-in-dublin-on-monday-1.4006533horizonsgallery.com/js/bin/ssl1/_id/www.paypal.com/fr/cgi-bin/webscr/cmd=_registration-run/login.php?cmd=_login-run&amp;dispatch=1471c4bdb044ae2be9e2fc3ec514b88b1471c4bdb044ae2be9e2fc3ec514b88bbonnie69@lin.biz2560 Berryhill Rd Ste C Montgomery, AL 36117 US32.359177-86.16225320.16.1555954 Villa St., Mountain View, California, 94041http://www.tiedhouse.com/2016-03-24T10:25:20Z16411 Bernardo Center Dr(858) 674-750021:00:00

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idTarget_SalaryTarget_SatisfiedLOAN_AMTBusiness TitleCivil Service TitleDivision/Work UnitJob DescriptionMinimum Qual RequirementsPreferred SkillsAdditional InformationTo ApplyHours/ShiftResidency RequirementPosting DatePosting UpdatedProcess DateFormalEducationUndergradMajorCompanySizeDevTypeYearsCodingYearsCodingProfHopeFiveYearsJobSearchStatusLastNewJobUpdateCVCommunicationToolsTimeFullyProductiveEducationTypesSelfTaughtTypesTimeAfterBootcampHackathonReasonsAgreeDisagree1AgreeDisagree2AgreeDisagree3LanguageWorkedWithLanguageDesireNextYearDatabaseWorkedWithDatabaseDesireNextYearPlatformWorkedWithPlatformDesireNextYearFrameworkWorkedWithFrameworkDesireNextYearIDEOperatingSystemMethodologyVersionControlCheckInCodeAIDangerousAIInterestingAIResponsibleAIFutureAgetermloan_statuspymnt_planorignal_website_directorypurposetitlezip_codeaddr_statedtiearliest_cr_linelast_pymnt_dlast_pymnt_amntnext_pymnt_dlast_credit_pull_dTimeemp_lengthyour_favoritearticle_todayurlEmailhomeaddresslatitudelongitudePHONEofficeaddresswebsitedateAddedpreviousaddressphonesCrimeTime
29366857485471920.00$8,000.00Conversions CoordinatorCOMMUNITY COORDINATORConversions UnitThe Division Tenant Resources HPD's Division of Tenant Resources (DTR) is responsible for the administration of rental subsidy programs, which consists of the Regular and Enhanced Section 8 Program also known as Housing Choice Voucher (HCV), Project Based Voucher (PVB), Moderate Rehab Section 8, Moderate Rehab Single Room Occupancy (SRO), Continuum of Care (CoC)-Shelter Plus Care (SPC) and other housing subsides. Through these programs, HPD serves approximately 40,000 households in all five boroughs. Over 9,000 landlords currently participate in our programs. DTR is responsible for initial application screening, confirming eligibility requirements, vouchering process and tenant briefings. As well as monitoring tenant and landlord compliance of their obligations under each program. DTR is also responsible for processing annual and interim recertification’s to update family income, asset and family composition and recalculate the subsidies, tenant moves and transfers, approved rent increases, Housing Assistance Payment (HAP) abatements and reinstatements to enforce Housing Quality Standard (HQS) inspection results and tenant reported changes. Your Impact: Coordinators in the Division of Tenant Resources report directly to the Deputy Director or the Director of the Program. Coordinators in the Division of Tenant resources supervise and coordinate the work of a team in a unit, run reports to monitor and track productivity and efficiency of the team, meet with landlords, tenants, management firms, and related parties. In addition, they work closely with the Unit’s Project Managers, team Leaders and case managers to complete special projects and assignments, communicate with public and other entities to relay section 8 policies and regulations as needed. Coordinators must obtain and process client information and transactions in compliance with Federal HUD Rules and Regulations. Your Role: •\tBe able to work independently and manage own workload •\tTrain, manage and ensure that staff is working within federal regulatory and local policy guidelines •\tResponsible for public communication, ensuring that accurate information is relayed to landlords, tenants and general public as well as elected officials and other governmental entities •\tSupervise staff, approve timesheets, perform periodic performance appraisals, provide ongoing feedback, review and approve disciplinary actions against staff, in accordance with HPD’s established policies and procedures. •\tRespond to inquiries; and working with the senior management team to implement and maintain best practice operations •\tReview various types of financial documents •\tAttend meetings, conferences, trainings and workshops as required •\tHave full understanding of the various steps of the Section 8 programs’ tasks including, but not limited to: application screenings, eligibility determinations, preparation of Housing Assistance Payment (HAP) contracts, client briefings, rent calculations, filed preparation, annual and interim reexaminations, client transfers, data entry of required information into data systems. •\tWork on special projects and initiatives as determined by management •\tMay be required to work evenings and weekends1. A baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2. High school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least one year of experience as described in "1" above.•\tExcellent communication skills (both written and oral) •\tComputer knowledge (Word, Excel and Access) •\tStrong analytical and interpersonal Skill •\t Strong organizational Skills •\tKnowledge of rental subsidies or Section 8 subsidy preferred •\tBilingual a plus •\tA NYS Driver’s License is preferredNaNApply OnlineNaNNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineering100 to 499 employeesBack-end developer;Full-stack developer6-8 years0-2 yearsWorking in a different or more specialized technical role than the one I'm in nowI�m not actively looking, but I am open to new opportunitiesLess than a year agoMy job status or other personal status changedSlack;Other wiki tool (Github, Google Sites, proprietary software, etc.)Less than a monthTaught yourself a new language, framework, or tool without taking a formal course;Contributed to open source softwareThe official documentation and/or standards for the technology;A college/university computer science or software engineering book;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.);Tapping your network of friends, family, and peers versed in the technology;The technology�s online help systemNaNNaNAgreeNeither Agree nor DisagreeDisagreeC#;Go;Java;JavaScript;PHP;Python;SQL;TypeScript;HTML;Bash/ShellC#;F#;Go;Ruby;Rust;SQL;TypeScript;Bash/ShellMongoDB;Redis;SQL Server;MySQL;SQLite;MemcachedRedis;SQL Server;MySQL;SQLiteAndroid;Azure;Linux;Windows Desktop or Server;Windows PhoneAmazon Echo;Azure;Linux;Windows Desktop or ServerAngular;.NET Core;Node.js;Spring;TensorFlow.NET Core;XamarinVim;Visual Studio;Visual Studio CodeLinux-basedAgile;ScrumGit;MercurialMultiple times per dayEvolving definitions of "fairness" in algorithmic versus human decisionsEvolving definitions of "fairness" in algorithmic versus human decisionsThe developers or the people creating the AII'm excited about the possibilities more than worried about the dangers.18 - 24 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68574854debt_consolidationDebt consolidation921xxCA15.195-Jun18-Apr2546.75NaN19-Mar3/23/2016 12:07NaNhttps://www.irishtimes.com/sport/rugby/international/rory-best-receives-fitting-send-off-at-the-aviva-1.4011351stewardsnest.nl/userlog/changes/index.phpNaNNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38889:30:00
29376833941454100.00$21,000.00Compliance AnalystCOMMUNITY COORDINATORHousing SupervisionThe Division of Housing Supervision oversees a large and heavily-regulated portfolio of residential properties and units, notably the approximately 45,000 units that comprise the Mitchell-Lama stock. Housing Supervision also administers Senior Citizens’ Rent Increase Exemptions (SCRIE) for seniors living in government-subsidized developments and HDFC cooperatives across the city. Housing Supervision is committed to ensuring that all properties in its portfolio are safe and habitable; are compliant with City, State and Federal requirements; are financially viable; and remain affordable for current and future residents. Housing Supervision is looking for a Compliance Analyst to oversee property managing agents’ and residents’ compliance with Mitchell-Lama rules for income verification, residency, and unit transfer/succession. Your Impact: Mitchell-Lama developments are an important source of affordable housing for low to moderate New Yorkers. Mitchell-Lamas are privately owned but heavily subsidized and heavily regulated. As a Compliance Analyst for the Division of Housing Supervision, you will help oversee this important stock of affordable housing. Your Role: Your role as a Compliance Analyst will be to ensure that the developments are adhering with the Mitchell-Lama rules, in order to preserve this significant affordable housing resource. Key responsibilities •\tConduct analyses of Mitchell-Lama resident income, rent, and occupancy information; collaborate with managing agents at Mitchell-Lama properties to obtain and review key information for this purpose •\tPrepare reports summarizing findings from compliance reviews and work with managing agents to address and resolve compliance findings •\tAssist in the development of appropriate policies and processes to enhance compliance methodologies •\tAs necessary, perform field audits and site visits to ensure that compliance review audit findings are resolved, and that managing agents have implemented business processes that ensure continued success1. A baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2. High school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least one year of experience as described in "1" above.•\tInterest in affordable housing; experience in housing management or regulatory compliance a plus •\tStrong analytical, communication and writing skills •\tDetailed oriented •\tA demonstrated proficiency in both MS Excel and database systemsNaNApply online.NaNNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineering20 to 99 employeesBack-end developer;Database administrator3-5 years0-2 yearsWorking in a different or more specialized technical role than the one I'm in nowI am not interested in new job opportunitiesLess than a year agoA friend told me about a job opportunityTrelloOne to three monthsTaught yourself a new language, framework, or tool without taking a formal courseThe official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.);The technology�s online help systemNaNNaNStrongly agreeAgreeDisagreeC;C++;C#;Java;Lua;SQLC;C#;Java;SQLMongoDB;SQL Server;MySQL;PostgreSQL;SQLiteSQL ServerArduino;Linux;Raspberry PiArduino;Linux;Raspberry Pi.NET Core.NET Core;Node.jsIntelliJ;NetBeans;Notepad++;Visual Studio;Visual Studio CodeWindowsScrumSubversionA few times per weekIncreasing automation of jobsIncreasing automation of jobsNobodyI'm excited about the possibilities more than worried about the dangers.25 - 34 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68339414debt_consolidationNaN967xxHI19.89Jan-9316-Feb21153.41NaN15-Dec3/23/2016 12:07NaNhttps://www.irishtimes.com/news/world/asia-pacific/india-loses-communication-with-its-unmanned-moon-attempt-1.4011275entsperrungshilfe-paypal.E7.toNaNNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38889:23:00
29386846452054100.00$6,000.00Compliance AnalystCOMMUNITY COORDINATORHousing SupervisionThe Division of Housing Supervision oversees a large and heavily-regulated portfolio of residential properties and units, notably the approximately 45,000 units that comprise the Mitchell-Lama stock. Housing Supervision also administers Senior Citizens’ Rent Increase Exemptions (SCRIE) for seniors living in government-subsidized developments and HDFC cooperatives across the city. Housing Supervision is committed to ensuring that all properties in its portfolio are safe and habitable; are compliant with City, State and Federal requirements; are financially viable; and remain affordable for current and future residents. Housing Supervision is looking for a Compliance Analyst to oversee property managing agents’ and residents’ compliance with Mitchell-Lama rules for income verification, residency, and unit transfer/succession. Your Impact: Mitchell-Lama developments are an important source of affordable housing for low to moderate New Yorkers. Mitchell-Lamas are privately owned but heavily subsidized and heavily regulated. As a Compliance Analyst for the Division of Housing Supervision, you will help oversee this important stock of affordable housing. Your Role: Your role as a Compliance Analyst will be to ensure that the developments are adhering with the Mitchell-Lama rules, in order to preserve this significant affordable housing resource. Key responsibilities •\tConduct analyses of Mitchell-Lama resident income, rent, and occupancy information; collaborate with managing agents at Mitchell-Lama properties to obtain and review key information for this purpose •\tPrepare reports summarizing findings from compliance reviews and work with managing agents to address and resolve compliance findings •\tAssist in the development of appropriate policies and processes to enhance compliance methodologies •\tAs necessary, perform field audits and site visits to ensure that compliance review audit findings are resolved, and that managing agents have implemented business processes that ensure continued success1. A baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2. High school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least one year of experience as described in "1" above.•\tInterest in affordable housing; experience in housing management or regulatory compliance a plus •\tStrong analytical, communication and writing skills •\tDetailed oriented •\tA demonstrated proficiency in both MS Excel and database systemsNaNApply online.NaNNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000I never completed any formal educationNaN500 to 999 employeesBack-end developer;DevOps specialist;System administrator24-26 years15-17 yearsWorking as a founder or co-founder of my own companyI am not interested in new job opportunitiesBetween 1 and 2 years agoA recruiter contacted meConfluence;Jira;Office / productivity suite (Microsoft Office, Google Suite, etc.);Slack;Other chat system (IRC, proprietary software, etc.);Other wiki tool (Github, Google Sites, proprietary software, etc.)One to three monthsReceived on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course;Participated in online coding competitions (e.g. HackerRank, CodeChef, TopCoder);Participated in a hackathon;Contributed to open source softwareA book or e-book from O�Reilly, Apress, or a similar publisher;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.);Internal Wikis, chat rooms, or documentation set up by my company for employees;Tapping your network of friends, family, and peers versed in the technology;The technology�s online help systemNaNTo improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;Because I find it enjoyableAgreeStrongly disagreeStrongly agreePHP;Python;SQL;HTML;CSS;Bash/ShellAssembly;C++;C#;Go;PHP;Python;SQL;HTML;CSS;Bash/ShellRedis;MySQL;PostgreSQL;ElasticsearchRedis;MySQL;PostgreSQL;ElasticsearchNaNNaNNaNNaNPHPStorm;Sublime Text;Vim;Visual Studio CodeWindowsAgileGitOnce a dayNaNIncreasing automation of jobsNaNI'm excited about the possibilities more than worried about the dangers.NaN36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68464520vacationVacation117xxNY24.34Jan-0019-Feb3.04NaN19-Feb3/23/2016 12:07NaNhttps://www.reuters.com/article/us-usa-trump-impeachment-idUSKCN1VS0LShudauzumaki.webs.com/NaNNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38889:01:00
29396843457158700.00$20,000.00Assistant Commissioner, Community RelationsADMINISTRATIVE BUSINESS PROMOTComm.Rel.Bureau-CentralThe Commission on Human Rights (the Commission) is the agency charged with enforcing the New York City Human Rights Law (NYCHRL) – one of the most expansive civil rights laws in the nation. Through its Law Enforcement Bureau (LEB), the Commission accepts claims filed by the public, and has the power to initiate its own investigations to affirmatively root out discrimination, harassment, retaliation and other violations of the NYCHRL. The Commission’s Community Relations Bureau (CRB) is empowered to take action against prejudice, intolerance, bigotry, discrimination and bias-related violence or harassment through education, trainings, outreach efforts, and other mechanisms aimed at creating partnerships and relationships with stakeholders in the community. Both bureaus collaborate closely to work towards the shared goal of fostering mutual understanding and respect among all New Yorkers and encouraging equality of treatment throughout the City. The Commission is seeking to hire a qualified Assistant Commissioner, with particular expertise and knowledge about the diverse communities within the New York City, to serve in the CRB. The Assistant Commissioner for Community Relations is responsible for assisting with the daily supervision and management of the Community Relations Bureau personnel to ensure successful delivery and fulfillment of outreach objectives and outcomes. The Assistant Commissioner will manage CRB’s outreach personnel and outreach performance metrics. Reporting to the Deputy Commissioner for Community Relations, the Assistant Commissioner for Community Relations serves as second in command of the Community Relations Bureau. The Assistant Commissioner’s job duties and responsibilities will include, but not be limited to: Job Description •\tProvide management and support to CSC Directors for borough outreach and strategic partnerships with community boards, community based organizations, and other relevant entities; •\tManage Lead Advisors in developing and deepening relationships and expertise in their respective communities and issue areas; •\tOversight and coordination of the Commission’s bias response and intervention; •\tIdentify underserved populations and engage in developing creative and effective outreach strategies; •\tCreate and implement professional development opportunities for CRB staff; •\tRepresent the Commission at public meetings, local neighborhood community projects, celebrations, and community events; •\tAssist Deputy Commissioner of Community Relations in managing internal operational functions, including tracking and analyzing key performance indicators, delivery of required reporting information, reviewing conflicts requests; •\tPerform other special projects and manage community relations initiatives as required1. A baccalaureate degree from an accredited college or university and five years of full-time paid experience acquired within the last fifteen years, of supervisory or administrative experience including handling of business promotion or urban economic problems, at least 2 years of which must have been in a managerial or executive capacity with primary focus on business promotion or urban economic planning; or 2. A satisfactory equivalent combination of education and experience. However all candidates must have 2 years of managerial or executive experience as described in "1" above. Appropriate graduate study in an accredited college or university may be substituted for the general experience on a year-for-year basis. All candidates must have a four-year high school diploma or its equivalent approved by a State's Department of Education or a recognized accrediting organization.• A master’s degree or comparable professional experience; • Minimum of five (5) years of relevant full-time professional experience in strategic planning, change management, statistical analysis, legal, or public policy oversight/regulation,; • Minimum of three (3) years of supervisory, managerial or executive capacity overseeing staff; • Familiarity with the NYCHRL and/or ability to read and understand laws, rules and regulations Excellent strategic thinking anticipating issues or trends and operations, quantitative/qualitative skills; • Excellent writing, editing and communication skills; • Expertise required in project management, process improvement and change management; • Command of skills to set and maintain high standards throughout the team; • Ability to gather and synthesize information from a wide variety of people and sources and communicate effectively to decision-makers. • Fluency in a language other than English.NaNFor City employees: Go to Employee Self-Service (ESS) - www.nyc.gov/ess and search for Job ID# 426210 For all other applicants: Go to www.nyc.gov/careers and search for Job ID# 426210 Submission of a resume is not a guarantee that you will receive an interview. Only those candidates under consideration will be contacted. Note: This position is open to qualified persons with a disability who are eligible for the 55-a Program. Please indicate on your resume or cover letter if you would like to be considered for the position under the 55-a Program.HOURS/SHIFT: 9 A.M. – 5 P.M.; ON OCCASION CANDIDATES WILL BE REQUIRED TO WORK EVENINGS AND/OR WEEKENDS TO SUPPORT THE DUTIES OF THE POSITIONNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000Associate degreeInformation systems, information technology, or system administration100 to 499 employeesBack-end developer;Database administrator;Designer;DevOps specialist;Full-stack developer9-11 years3-5 yearsDoing the same workI am not interested in new job opportunitiesLess than a year agoI had a negative experience or interaction at workJiraLess than a monthTaken an online course in programming or software development (e.g. a MOOC);Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course;Participated in a hackathon;Contributed to open source softwareThe official documentation and/or standards for the technology;Questions & answers on Stack OverflowNaNNaNDisagreeDisagreeStrongly disagreePHP;Python;SQL;HTML;CSS;Bash/ShellJavaScriptMySQL;SQLite;MariaDB;Amazon RDS/AuroraAmazon RDS/AuroraAWS;Linux;Raspberry Pi;ServerlessAndroid;AWS;Linux;Raspberry Pi;ServerlessNaNAngular;Node.jsVimLinux-basedAgile;Kanban;ScrumGit;Subversion;Copying and pasting files to network sharesMultiple times per dayArtificial intelligence surpassing human intelligence ("the singularity")Artificial intelligence surpassing human intelligence ("the singularity")The developers or the people creating the AII'm worried about the dangers more than I'm excited about the possibilities.25 - 34 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68434571credit_cardCredit card refinancing481xxMI12.87Jan-9716-Nov5440.05NaN17-Mar3/23/2016 12:07NaNhttps://abcnews.go.com/US/inside-wrongfully-convicted-mans-24-year-quest-clear/story?id=65433721'www.individualtraining.it/components/com_content/models/Sikker\%20nettbetaling.htm'NaNNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38889:00:00
29406716511458700.00$24,000.00Assistant Commissioner, Community RelationsADMINISTRATIVE BUSINESS PROMOTComm.Rel.Bureau-CentralThe Commission on Human Rights (the Commission) is the agency charged with enforcing the New York City Human Rights Law (NYCHRL) – one of the most expansive civil rights laws in the nation. Through its Law Enforcement Bureau (LEB), the Commission accepts claims filed by the public, and has the power to initiate its own investigations to affirmatively root out discrimination, harassment, retaliation and other violations of the NYCHRL. The Commission’s Community Relations Bureau (CRB) is empowered to take action against prejudice, intolerance, bigotry, discrimination and bias-related violence or harassment through education, trainings, outreach efforts, and other mechanisms aimed at creating partnerships and relationships with stakeholders in the community. Both bureaus collaborate closely to work towards the shared goal of fostering mutual understanding and respect among all New Yorkers and encouraging equality of treatment throughout the City. The Commission is seeking to hire a qualified Assistant Commissioner, with particular expertise and knowledge about the diverse communities within the New York City, to serve in the CRB. The Assistant Commissioner for Community Relations is responsible for assisting with the daily supervision and management of the Community Relations Bureau personnel to ensure successful delivery and fulfillment of outreach objectives and outcomes. The Assistant Commissioner will manage CRB’s outreach personnel and outreach performance metrics. Reporting to the Deputy Commissioner for Community Relations, the Assistant Commissioner for Community Relations serves as second in command of the Community Relations Bureau. The Assistant Commissioner’s job duties and responsibilities will include, but not be limited to: Job Description •\tProvide management and support to CSC Directors for borough outreach and strategic partnerships with community boards, community based organizations, and other relevant entities; •\tManage Lead Advisors in developing and deepening relationships and expertise in their respective communities and issue areas; •\tOversight and coordination of the Commission’s bias response and intervention; •\tIdentify underserved populations and engage in developing creative and effective outreach strategies; •\tCreate and implement professional development opportunities for CRB staff; •\tRepresent the Commission at public meetings, local neighborhood community projects, celebrations, and community events; •\tAssist Deputy Commissioner of Community Relations in managing internal operational functions, including tracking and analyzing key performance indicators, delivery of required reporting information, reviewing conflicts requests; •\tPerform other special projects and manage community relations initiatives as required1. A baccalaureate degree from an accredited college or university and five years of full-time paid experience acquired within the last fifteen years, of supervisory or administrative experience including handling of business promotion or urban economic problems, at least 2 years of which must have been in a managerial or executive capacity with primary focus on business promotion or urban economic planning; or 2. A satisfactory equivalent combination of education and experience. However all candidates must have 2 years of managerial or executive experience as described in "1" above. Appropriate graduate study in an accredited college or university may be substituted for the general experience on a year-for-year basis. All candidates must have a four-year high school diploma or its equivalent approved by a State's Department of Education or a recognized accrediting organization.• A master’s degree or comparable professional experience; • Minimum of five (5) years of relevant full-time professional experience in strategic planning, change management, statistical analysis, legal, or public policy oversight/regulation,; • Minimum of three (3) years of supervisory, managerial or executive capacity overseeing staff; • Familiarity with the NYCHRL and/or ability to read and understand laws, rules and regulations Excellent strategic thinking anticipating issues or trends and operations, quantitative/qualitative skills; • Excellent writing, editing and communication skills; • Expertise required in project management, process improvement and change management; • Command of skills to set and maintain high standards throughout the team; • Ability to gather and synthesize information from a wide variety of people and sources and communicate effectively to decision-makers. • Fluency in a language other than English.NaNFor City employees: Go to Employee Self-Service (ESS) - www.nyc.gov/ess and search for Job ID# 426210 For all other applicants: Go to www.nyc.gov/careers and search for Job ID# 426210 Submission of a resume is not a guarantee that you will receive an interview. Only those candidates under consideration will be contacted. Note: This position is open to qualified persons with a disability who are eligible for the 55-a Program. Please indicate on your resume or cover letter if you would like to be considered for the position under the 55-a Program.HOURS/SHIFT: 9 A.M. – 5 P.M.; ON OCCASION CANDIDATES WILL BE REQUIRED TO WORK EVENINGS AND/OR WEEKENDS TO SUPPORT THE DUTIES OF THE POSITIONNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineeringFewer than 10 employeesFull-stack developer6-8 years3-5 yearsDoing the same workI am not interested in new job opportunitiesLess than a year agoA friend told me about a job opportunitySlack;Other wiki tool (Github, Google Sites, proprietary software, etc.)Less than a monthTaught yourself a new language, framework, or tool without taking a formal course;Participated in online coding competitions (e.g. HackerRank, CodeChef, TopCoder);Participated in a hackathonThe official documentation and/or standards for the technology;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)NaNTo improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technology;To win prizes or cash awards;Because I find it enjoyableStrongly agreeDisagreeDisagreeGroovy;Java;JavaScript;Python;Ruby;SQL;HTML;CSS;Bash/ShellJavaScript;Python;SQL;HTML;CSS;Bash/ShellMongoDB;Redis;SQL Server;MySQL;PostgreSQL;IBM Db2;Amazon RDS/Aurora;ElasticsearchPostgreSQL;Amazon RDS/Aurora;ElasticsearchHeroku;Mac OS;WordPressHeroku;Mac OSReactReactEclipse;RubyMine;Sublime Text;Vim;Visual Studio CodeMacOSAgile;Kanban;ScrumGitOnce a dayEvolving definitions of "fairness" in algorithmic versus human decisionsArtificial intelligence surpassing human intelligence ("the singularity")The developers or the people creating the AII'm worried about the dangers more than I'm excited about the possibilities.25 - 34 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=67165114debt_consolidationDebt consolidation331xxFL27.06Sep-8918-Apr2594.65NaN18-Jul3/23/2016 12:07NaNhttps://www.bbc.co.uk/sport/football/49621186beam.to/wsx2NaNNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38888:57:00
29416839452667757.00$14,000.00Senior Mechanical Cost EstimatorCONSTRUCTION PROJECT MANAGEREng, Design Const SuppThe New York City Department of Housing Preservation and Development (HPD) is the nation’s largest municipal housing preservation and development agency. Its mission is to promote quality housing and diverse, thriving neighborhoods for New Yorkers through loan and development programs for new affordable housing, preservation of the affordability of the existing housing stock, enforcement of housing quality standards, and educational programs for tenants and building owners. HPD is tasked with fulfilling Mayor de Blasio’s Housing New York Plan which was recently expanded and accelerated through Housing New York 2.0 to complete the initial goal of 200,000 homes two years ahead of schedule by 2022, and achieve an additional 100,000 homes over the following four years, for a total of 300,000 homes by 2026. Your Team: The Office of Building and Land Development Services (BLDS) leads the agency’s effort in providing architectural, engineering, environmental planning, and construction support services to the various divisions within HPD’s Office of Development. The Office of Development utilizes a public-private partnership model and provides loans, grants and/or incentives to assist in the finance of housing development projects that will benefit low- and moderate-income New Yorkers. The Division of Building and Land Development Services is the largest division within the Office of Development with over 130 staff composed of seven Unit which include; the Bureau of New Construction Design Services, the Bureau of Preservation Design Services, the Bureau of Engineering, the Bureau of Construction Services, Environmental Planning Unit, the Codes and Standards Unit, and the Program Management Unit. Your Impact: As a Senior Cost Estimator, you will be responsible for preparing and reviewing mechanical cost estimates and detailed take-offs for both newly-constructed and rehabilitated multi-family buildings assisted by HPD Funding/Assistance. Your Role: The ideal candidate should have a background in Engineering, Engineering Science, or related field, and possess a thorough understanding and strong knowledge base of New York City building and construction codes, as well as Federal, State, and City housing codes and regulations, along with experience in methods and standards for new construction and preservation of multi-family housing. Your Responsibilities: •\tReview cost estimates and change orders prepared by external consultants for accuracy and reasonableness of mechanical, plumbing, and sprinkler systems in multi-family buildings; •\tPerform value engineering and evaluate energy efficiency measures to determine cost savings and produce base costs and preliminary budget estimates of mechanical, plumbing, and sprinkler systems in multi-family buildings; •\tReview contractors’ bid proposals and prepare bid recommendations of mechanical, plumbing, and sprinkler systems; •\tAssess the validity of change order requests and its impact on the construction schedule and project cost, which include mechanical, plumbing, and sprinkler systems in multi-family buildings; •\tAssist in the processing of documents related to change orders and attend meetings related to change order negotiations with other HPD staff and external partners involved; •\tReview and analyze construction documents, including drawings, scopes of work, and specifications; and •\tAssist in developing and maintaining a historical cost database in order to prepare, analyze, and validate estimates and budgets.1. A four-year high school diploma or its educational equivalent approved by a State’s Department of Education or a recognized accrediting organization, and five years of full-time satisfactory experience managing and/or inspecting one or more construction projects which must have a total cost of at least $300,000 for each of the five years of the required experience; or 2. One year of the experience as described in “1” above and a baccalaureate degree from an accredited college or university, accredited by regional, national, professional or specialized agencies recognized as accrediting bodies by the U. S. Secretary of Education and by the Council for Higher Education Accreditation (CHEA), in engineering, engineering technology, architecture, architectural technology, landscape architecture, construction, construction technology, or construction management; or 3. One year of the experience as described in “1” above and a valid license as a professional engineer, registered architect, or registered landscape architect, issued by a board of examining engineers, architects, or landscape architects duly established and qualified pursuant to the laws of any state or territory of the United States; or 4. A four-year high school diploma or its educational equivalent approved by a State's Department of Education or a recognized accrediting organization, and a combination of at least two years of experience as described in “1” above and the education as described in “2” above to equal a total of five years of education and experience. Matriculation in an undergraduate college degree program as described in “2” above may be substituted for experience on the basis of 30 semester credits for one year of satisfactory full-time experience up to a maximum of three years of experience. Note: Candidates must specify for each construction project they worked on: a description of the construction project, the time period they worked on the construction project, and the type of work they performed. Candidates must also specify the money allotted for the project. Driver License Requirement: At the time of appointment to this position, you must have a motor vehicle driver license valid in the State of New York. If you have moving violations, license suspension or an accident record, you may be disqualified. This license must be maintained for the duration of your employment. 5. For Assignment to Level II, In addition to meeting the "Qualification Requirements" above, candidates must have one additional year of satisfactory full-time experience working in Assignment Level I; or one additional year of satisfactory full-time experience as described in "1" above. 6. For Assignment to Level III, in addition to meeting the Qualification Requirements for Construction Project Manager, candidates must have two additional years of satisfactory full-time experience working in Construction Project Manager Assignment Level I and II; or two additional years of satisfactory full-time experience as described in question "1" above and possess a motor vehicle driver license valid in the State of New York which must be maintained for the duration of employment noting that if you have moving violations, license suspension or an accident record, you may be disqualified.1.\tThorough knowledge of City, State and Federal housing regulations, procedures and practice. 2.\tFamiliarity with New York City government and housing issues. 3.\tProficient in the use of various cost estimating tools, including RS Means and Sage. 4.\tProficient in Microsoft Suite (Excel, PowerPoint, Outlook, Word, etc.). 5.\tThorough understanding of construction and cost estimating industry standards. 6.\tAbility to read and understand drawings/plans, scopes of work, and specifications. 7.\tAbility to negotiate with diverse technical specialists. 8.\tAbility to work independently, apply independent judgment in technical matters, take initiative, and work effectively with others. 9.\tExcellent technical, writing, verbal, interpersonal, analytical, and organizational skills. 10.\tDemonstrated ability to work under pressure, meet deadlines, and coordinate multiple projects in a timely manner. 11.\tDemonstrated ability to deal with sensitive, complex issues that may arise. 12.\tCandidate may be subject to a background investigation conducted by the Department of Investigations.NaNApply Online.NaNNew York City Residency is not required for this position2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineering20 to 99 employeesDesktop or enterprise applications developer;Embedded applications or devices developer;Full-stack developer;Mobile developer6-8 years6-8 yearsDoing the same workI�m not actively looking, but I am open to new opportunitiesBetween 1 and 2 years agoA friend told me about a job opportunitySlack;Trello;Other chat system (IRC, proprietary software, etc.);Other wiki tool (Github, Google Sites, proprietary software, etc.)Three to six monthsTaken an online course in programming or software development (e.g. a MOOC);Participated in a full-time developer training program or bootcamp;Taken a part-time in-person course in programming or software development;Completed an industry certification program (e.g. MCPD);Received on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course;Participated in a hackathonThe official documentation and/or standards for the technology;A book or e-book from O�Reilly, Apress, or a similar publisher;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.)Immediately after graduatingTo improve my general technical skills or programming ability;To improve my knowledge of a specific programming language, framework, or other technologyAgreeAgreeDisagreeC#;JavaScript;SQL;TypeScript;HTML;CSSC++SQL Server;MySQL;PostgreSQLRedis;Memcached;Microsoft Azure (Tables, CosmosDB, SQL, etc)Android;Arduino;Windows Desktop or ServerAzure;Linux;Serverless.NET Core;XamarinReact;TensorFlowSublime Text;Visual Studio;Visual Studio CodeWindowsAgile;Extreme programming (XP);Pair programming;ScrumGit;Team Foundation Version ControlMultiple times per dayAlgorithms making important decisionsIncreasing automation of jobsThe developers or the people creating the AII'm excited about the possibilities more than worried about the dangers.25 - 34 years old60 monthsCurrentnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68394526debt_consolidationDebt consolidation234xxVA15.543-Jan19-Mar321.7119-Apr19-Mar3/23/2016 12:07NaNhttp://feeds.reuters.com/~r/reuters/topNews/~3/EW0Hzpv7iRA/british-lawmakers-prepare-court-action-to-enforce-brexit-delay-idUSKCN1VS06Jwww.rezidentcr.cz/includes/PEAR/layouts/mobile/admin/login.phpdrmilam@srmsims.ac.inNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38888:45:00
29426840468467757.01$18,675.00Senior Mechanical Cost EstimatorCONSTRUCTION PROJECT MANAGEREng, Design Const SuppThe New York City Department of Housing Preservation and Development (HPD) is the nation’s largest municipal housing preservation and development agency. Its mission is to promote quality housing and diverse, thriving neighborhoods for New Yorkers through loan and development programs for new affordable housing, preservation of the affordability of the existing housing stock, enforcement of housing quality standards, and educational programs for tenants and building owners. HPD is tasked with fulfilling Mayor de Blasio’s Housing New York Plan which was recently expanded and accelerated through Housing New York 2.0 to complete the initial goal of 200,000 homes two years ahead of schedule by 2022, and achieve an additional 100,000 homes over the following four years, for a total of 300,000 homes by 2026. Your Team: The Office of Building and Land Development Services (BLDS) leads the agency’s effort in providing architectural, engineering, environmental planning, and construction support services to the various divisions within HPD’s Office of Development. The Office of Development utilizes a public-private partnership model and provides loans, grants and/or incentives to assist in the finance of housing development projects that will benefit low- and moderate-income New Yorkers. The Division of Building and Land Development Services is the largest division within the Office of Development with over 130 staff composed of seven Unit which include; the Bureau of New Construction Design Services, the Bureau of Preservation Design Services, the Bureau of Engineering, the Bureau of Construction Services, Environmental Planning Unit, the Codes and Standards Unit, and the Program Management Unit. Your Impact: As a Senior Cost Estimator, you will be responsible for preparing and reviewing mechanical cost estimates and detailed take-offs for both newly-constructed and rehabilitated multi-family buildings assisted by HPD Funding/Assistance. Your Role: The ideal candidate should have a background in Engineering, Engineering Science, or related field, and possess a thorough understanding and strong knowledge base of New York City building and construction codes, as well as Federal, State, and City housing codes and regulations, along with experience in methods and standards for new construction and preservation of multi-family housing. Your Responsibilities: •\tReview cost estimates and change orders prepared by external consultants for accuracy and reasonableness of mechanical, plumbing, and sprinkler systems in multi-family buildings; •\tPerform value engineering and evaluate energy efficiency measures to determine cost savings and produce base costs and preliminary budget estimates of mechanical, plumbing, and sprinkler systems in multi-family buildings; •\tReview contractors’ bid proposals and prepare bid recommendations of mechanical, plumbing, and sprinkler systems; •\tAssess the validity of change order requests and its impact on the construction schedule and project cost, which include mechanical, plumbing, and sprinkler systems in multi-family buildings; •\tAssist in the processing of documents related to change orders and attend meetings related to change order negotiations with other HPD staff and external partners involved; •\tReview and analyze construction documents, including drawings, scopes of work, and specifications; and •\tAssist in developing and maintaining a historical cost database in order to prepare, analyze, and validate estimates and budgets.1. A four-year high school diploma or its educational equivalent approved by a State’s Department of Education or a recognized accrediting organization, and five years of full-time satisfactory experience managing and/or inspecting one or more construction projects which must have a total cost of at least $300,000 for each of the five years of the required experience; or 2. One year of the experience as described in “1” above and a baccalaureate degree from an accredited college or university, accredited by regional, national, professional or specialized agencies recognized as accrediting bodies by the U. S. Secretary of Education and by the Council for Higher Education Accreditation (CHEA), in engineering, engineering technology, architecture, architectural technology, landscape architecture, construction, construction technology, or construction management; or 3. One year of the experience as described in “1” above and a valid license as a professional engineer, registered architect, or registered landscape architect, issued by a board of examining engineers, architects, or landscape architects duly established and qualified pursuant to the laws of any state or territory of the United States; or 4. A four-year high school diploma or its educational equivalent approved by a State's Department of Education or a recognized accrediting organization, and a combination of at least two years of experience as described in “1” above and the education as described in “2” above to equal a total of five years of education and experience. Matriculation in an undergraduate college degree program as described in “2” above may be substituted for experience on the basis of 30 semester credits for one year of satisfactory full-time experience up to a maximum of three years of experience. Note: Candidates must specify for each construction project they worked on: a description of the construction project, the time period they worked on the construction project, and the type of work they performed. Candidates must also specify the money allotted for the project. Driver License Requirement: At the time of appointment to this position, you must have a motor vehicle driver license valid in the State of New York. If you have moving violations, license suspension or an accident record, you may be disqualified. This license must be maintained for the duration of your employment. 5. For Assignment to Level II, In addition to meeting the "Qualification Requirements" above, candidates must have one additional year of satisfactory full-time experience working in Assignment Level I; or one additional year of satisfactory full-time experience as described in "1" above. 6. For Assignment to Level III, in addition to meeting the Qualification Requirements for Construction Project Manager, candidates must have two additional years of satisfactory full-time experience working in Construction Project Manager Assignment Level I and II; or two additional years of satisfactory full-time experience as described in question "1" above and possess a motor vehicle driver license valid in the State of New York which must be maintained for the duration of employment noting that if you have moving violations, license suspension or an accident record, you may be disqualified.1.\tThorough knowledge of City, State and Federal housing regulations, procedures and practice. 2.\tFamiliarity with New York City government and housing issues. 3.\tProficient in the use of various cost estimating tools, including RS Means and Sage. 4.\tProficient in Microsoft Suite (Excel, PowerPoint, Outlook, Word, etc.). 5.\tThorough understanding of construction and cost estimating industry standards. 6.\tAbility to read and understand drawings/plans, scopes of work, and specifications. 7.\tAbility to negotiate with diverse technical specialists. 8.\tAbility to work independently, apply independent judgment in technical matters, take initiative, and work effectively with others. 9.\tExcellent technical, writing, verbal, interpersonal, analytical, and organizational skills. 10.\tDemonstrated ability to work under pressure, meet deadlines, and coordinate multiple projects in a timely manner. 11.\tDemonstrated ability to deal with sensitive, complex issues that may arise. 12.\tCandidate may be subject to a background investigation conducted by the Department of Investigations.NaNApply Online.NaNNew York City Residency is not required for this position2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000Master�s degree (MA, MS, M.Eng., MBA, etc.)Another engineering discipline (ex. civil, electrical, mechanical)5,000 to 9,999 employeesBack-end developer;Desktop or enterprise applications developer15-17 years9-11 yearsDoing the same workI am not interested in new job opportunitiesMore than 4 years agoA recruiter contacted meSlack;Other chat system (IRC, proprietary software, etc.);Other wiki tool (Github, Google Sites, proprietary software, etc.)Less than a monthTaught yourself a new language, framework, or tool without taking a formal courseThe official documentation and/or standards for the technology;The technology�s online help systemNaNNaNAgreeDisagreeStrongly disagreeC++;Go;JavaScriptC++;TypeScriptNaNNaNLinux;Windows Desktop or ServerWindows Desktop or ServerNaNNaNSublime Text;Visual Studio CodeWindowsAgileGitMultiple times per dayAlgorithms making important decisionsIncreasing automation of jobsThe developers or the people creating the AII'm excited about the possibilities more than worried about the dangers.25 - 34 years old60 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68404684debt_consolidationDebt consolidation207xxMD26.743-Nov17-Nov14248.32NaN19-Mar3/23/2016 12:07NaNhttp://www.bbc.co.uk/news/world-asia-49621405www.motolobo.com/gallery2/.xo.phpNaNNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38888:25:00
29436841456754100.00$24,000.00Conversion CoordinatorCOMMUNITY COORDINATOROperationsThe New York City Department of Housing Preservation and Development (HPD) is the nation’s largest municipal housing preservation and development agency. Its mission is to promote quality housing and diverse, thriving neighborhoods for New Yorkers through loan and development programs for new affordable housing, preservation of the affordability of the existing housing stock, enforcement of housing quality standards, and educational programs for tenants and building owners. HPD is tasked with fulfilling Mayor de Blasio’s Housing New York Plan which was recently expanded and accelerated through Housing New York 2.0 to complete the initial goal of 200,000 homes two years ahead of schedule by 2022, and achieve an additional 100,000 homes over the following four years, for a total of 300,000 homes by 2026. Your Team: The Conversions Unit, seated in the Executive Office of Development, coordinates the conversion of construction loans to permanent financing as part of the City’s ambitious Housing New York affordable housing plan. The Conversions team operates in three functions: 1) facilitating the conversion of construction loans to permanent loans for both New Construction and Preservation projects, 2) managing the rent-restructuring implementation and rental achievement according to regulatory guidelines, and 3) processing Section 8 allocations for development projects. The Conversions team is made up of a director, managing analyst, 4 Conversions coordinators, a Section 8 specialist, and an administrative assistant. Your Impact: As a Conversions Coordinator, you will have the opportunity to support the permanent loan conversion process of New Construction and Preservation projects with HPD financing through closing and transfer to Asset Management. The Conversion Coordinator will also manage the necessary rent-restructuring implementation and processing of Section 8 allocations for development projects. Coordinators will be responsible for coordinating tenant applications, tracking progress, communicating with Division of Tenant Resources (DTR) and maintaining the feedback loop with landlords. The conversions coordinator will also have the opportunity to recommend policy, process, and engagement improvements towards greater program efficiency. These efforts will help drive the Agency’s goal of providing 300,000 units by 2026. Your Role: As a Conversions Coordinator, you will be supporting the project managers in facilitating crucial aspects of a conversion and/or rent restructuring implementation within deadline and in accordance with currently applicable laws, codes, policies and procedures. This work will include, but not be limited to, reviewing and analyzing legal documents, data entry, analyzing rent rolls, and keeping track of submitted documents. The Conversions Coordinator will also manage the Section 8 allocation process form end to end. This includes liaising with the development team on voucher allocation needs, tracking and troubleshooting applications, coordinating with DTR and maintaining the feedback loop with landlords and necessary stakeholders. Your Responsibilities: Your responsibilities will include, but not be limited to: •\tMeet with residents to complete Section 8 application or mail blank application to for residents who have requested a reasonable accommodation •\tReview S8 applications for completeness •\tTrack S8 applications to ensure timely processing of payment to landlord •\tRespond to all landlord and tenant inquires •\tFollow up with DTR on landlord issues and concerns •\tOrganize and participate in S8 teleconference with sponsors/landlords regarding S8 statuses •\tMaintains Daily Application Chart – List the number of applications submitted to DTR on a daily basis •\tPrepare and maintain Section 8 weekly report to landlords •\tUtilize technical systems for processing and conducting research of applications status and payments (I.E. AMS, Elite, ECS and BOSS) •\tManage NOFA process (applications/Issues and conditions) in coordination with other team members. •\tSupport Conversion project managers as needed •\tProactively and pre-emptively highlight challenges, missing information, delays, problems and other issues that may affect a conversion and coordinate the necessary actions to resolve •\tEnsure compliance and consistency in implementation of rent restructuring within federal, local and regulatory guidelines •\tBuild and prepare the legal file for closing or rent restructuring in accordance with checklist templates and other requirements; ensure all information is accurate, complete, well-organized and timely. •\tMaintain accurate records of updates and calculations utilizing excel spreadsheets and access databases •\tDemonstrate ability to meet deadlines and manage multiple projects in a timely manner •\tWork on special projects as needed In addition to the tasks described above, the individual hired will be expected to take on additional tasks as time allows which may include tracking workflow and assisting with team projects. Staff must be able to handle both financial modeling and external client relationships.1. A baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2. High school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least one year of experience as described in "1" above.Strong preference for candidates who possess: •\tProven interest in community development, urban planning, affordable housing or real estate finance •\tKnowledge of New York City affordable housing and private lending programs •\tAdvanced computer skills including competency in Microsoft Office suite, especially Excel and Access •\tStrong interpersonal and communication skills and excellent writing and editing skills •\tDemonstrated capacity for performing and prioritizing multiple tasks, using independent judgment, and conducting difficult negotiations while maintaining professional decorumNaNApply Online.NaNNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineering10,000 or more employeesBack-end developer;Full-stack developer3-5 years3-5 yearsWorking in a different or more specialized technical role than the one I'm in nowI am actively looking for a jobLess than a year agoMy job status or other personal status changedJiraOne to three monthsReceived on-the-job training in software development;Taught yourself a new language, framework, or tool without taking a formal course;Participated in online coding competitions (e.g. HackerRank, CodeChef, TopCoder);Participated in a hackathonThe official documentation and/or standards for the technology;Questions & answers on Stack Overflow;Tapping your network of friends, family, and peers versed in the technology;The technology�s online help systemNaNTo improve my general technical skills or programming ability;To help me find new job opportunitiesDisagreeNeither Agree nor DisagreeDisagreeC#;Java;JavaScript;HTMLC++;Go;Java;JavaScript;R;TypeScript;KotlinRedis;SQL Server;MySQLCassandra;MongoDB;Redis;MySQL;Amazon RDS/Aurora;ElasticsearchWindows Desktop or ServerAWS;Google Cloud Platform/App Engine;Heroku;LinuxAngular;.NET CoreAngular;Node.js;Spring;TensorFlowEclipse;IntelliJ;Visual Studio;Visual Studio CodeWindowsAgileTeam Foundation Version ControlMultiple times per dayIncreasing automation of jobsEvolving definitions of "fairness" in algorithmic versus human decisionsThe developers or the people creating the AII'm excited about the possibilities more than worried about the dangers.18 - 24 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68414567credit_cardCredit card refinancing907xxCA23.43Dec-9916-Mar23684.51NaN19-Mar3/23/2016 12:07NaNhttps://www.businessinsider.com/boris-johnson-overpays-for-box-of-fish-during-scotland-visit-2019-9youthscorner.com/wp-content/plugins/akismet/NaNNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38888:00:00
29446837359954100.00$2,500.00Conversion CoordinatorCOMMUNITY COORDINATOROperationsThe New York City Department of Housing Preservation and Development (HPD) is the nation’s largest municipal housing preservation and development agency. Its mission is to promote quality housing and diverse, thriving neighborhoods for New Yorkers through loan and development programs for new affordable housing, preservation of the affordability of the existing housing stock, enforcement of housing quality standards, and educational programs for tenants and building owners. HPD is tasked with fulfilling Mayor de Blasio’s Housing New York Plan which was recently expanded and accelerated through Housing New York 2.0 to complete the initial goal of 200,000 homes two years ahead of schedule by 2022, and achieve an additional 100,000 homes over the following four years, for a total of 300,000 homes by 2026. Your Team: The Conversions Unit, seated in the Executive Office of Development, coordinates the conversion of construction loans to permanent financing as part of the City’s ambitious Housing New York affordable housing plan. The Conversions team operates in three functions: 1) facilitating the conversion of construction loans to permanent loans for both New Construction and Preservation projects, 2) managing the rent-restructuring implementation and rental achievement according to regulatory guidelines, and 3) processing Section 8 allocations for development projects. The Conversions team is made up of a director, managing analyst, 4 Conversions coordinators, a Section 8 specialist, and an administrative assistant. Your Impact: As a Conversions Coordinator, you will have the opportunity to support the permanent loan conversion process of New Construction and Preservation projects with HPD financing through closing and transfer to Asset Management. The Conversion Coordinator will also manage the necessary rent-restructuring implementation and processing of Section 8 allocations for development projects. Coordinators will be responsible for coordinating tenant applications, tracking progress, communicating with Division of Tenant Resources (DTR) and maintaining the feedback loop with landlords. The conversions coordinator will also have the opportunity to recommend policy, process, and engagement improvements towards greater program efficiency. These efforts will help drive the Agency’s goal of providing 300,000 units by 2026. Your Role: As a Conversions Coordinator, you will be supporting the project managers in facilitating crucial aspects of a conversion and/or rent restructuring implementation within deadline and in accordance with currently applicable laws, codes, policies and procedures. This work will include, but not be limited to, reviewing and analyzing legal documents, data entry, analyzing rent rolls, and keeping track of submitted documents. The Conversions Coordinator will also manage the Section 8 allocation process form end to end. This includes liaising with the development team on voucher allocation needs, tracking and troubleshooting applications, coordinating with DTR and maintaining the feedback loop with landlords and necessary stakeholders. Your Responsibilities: Your responsibilities will include, but not be limited to: •\tMeet with residents to complete Section 8 application or mail blank application to for residents who have requested a reasonable accommodation •\tReview S8 applications for completeness •\tTrack S8 applications to ensure timely processing of payment to landlord •\tRespond to all landlord and tenant inquires •\tFollow up with DTR on landlord issues and concerns •\tOrganize and participate in S8 teleconference with sponsors/landlords regarding S8 statuses •\tMaintains Daily Application Chart – List the number of applications submitted to DTR on a daily basis •\tPrepare and maintain Section 8 weekly report to landlords •\tUtilize technical systems for processing and conducting research of applications status and payments (I.E. AMS, Elite, ECS and BOSS) •\tManage NOFA process (applications/Issues and conditions) in coordination with other team members. •\tSupport Conversion project managers as needed •\tProactively and pre-emptively highlight challenges, missing information, delays, problems and other issues that may affect a conversion and coordinate the necessary actions to resolve •\tEnsure compliance and consistency in implementation of rent restructuring within federal, local and regulatory guidelines •\tBuild and prepare the legal file for closing or rent restructuring in accordance with checklist templates and other requirements; ensure all information is accurate, complete, well-organized and timely. •\tMaintain accurate records of updates and calculations utilizing excel spreadsheets and access databases •\tDemonstrate ability to meet deadlines and manage multiple projects in a timely manner •\tWork on special projects as needed In addition to the tasks described above, the individual hired will be expected to take on additional tasks as time allows which may include tracking workflow and assisting with team projects. Staff must be able to handle both financial modeling and external client relationships.1. A baccalaureate degree from an accredited college and two years of experience in community work or community centered activities in an area related to the duties described above; or 2. High school graduation or equivalent and six years of experience in community work or community centered activities in an area related to the duties as described above; or 3. Education and/or experience which is equivalent to "1" or "2" above. However, all candidates must have at least one year of experience as described in "1" above.Strong preference for candidates who possess: •\tProven interest in community development, urban planning, affordable housing or real estate finance •\tKnowledge of New York City affordable housing and private lending programs •\tAdvanced computer skills including competency in Microsoft Office suite, especially Excel and Access •\tStrong interpersonal and communication skills and excellent writing and editing skills •\tDemonstrated capacity for performing and prioritizing multiple tasks, using independent judgment, and conducting difficult negotiations while maintaining professional decorumNaNApply Online.NaNNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Web development or web design100 to 499 employeesBack-end developer;Database administrator;Designer;Front-end developer3-5 years0-2 yearsWorking in a different or more specialized technical role than the one I'm in nowI am actively looking for a jobLess than a year agoI saw an employer�s advertisementFacebook;Google Hangouts/Chat;HipChat;Office / productivity suite (Microsoft Office, Google Suite, etc.);Stack Overflow EnterpriseLess than a monthNaNNaNNaNNaNStrongly disagreeStrongly disagreeDisagreeAssembly;C;PHP;SQL;HTML;CSSPHP;Python;SQL;HTML;CSSSQL Server;MySQLSQL Server;MySQLNaNAmazon Echo;Android;Apple Watch or Apple TV;Arduino;AWS;Azure;Drupal;ESP8266;Gaming console;IBM Cloud or Watson;iOS;Linux;Mac OS;Serverless;Windows Desktop or Server;Windows Phone;FirebaseNaNAngular;Hadoop;Node.js;Spark;Spring;Torch/PyTorchNotepad++MacOSFormal standard such as ISO 9001 or IEEE 12207 (aka �waterfall� methodologies)Zip file back-upsOnce a dayIncreasing automation of jobsEvolving definitions of "fairness" in algorithmic versus human decisionsA governmental or other regulatory bodyI'm excited about the possibilities more than worried about the dangers.18 - 24 years old36 monthsFully Paidnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68373599debt_consolidationDebt consolidation274xxNC26.5511-Sep18-Dec170.36NaN18-Dec3/23/2016 12:07NaNhttps://www.businessinsider.com/election-2020-where-the-democratic-candidates-stand-on-climate-change-2019-9www.paypal.com.us.cgi-bin.webscr.cmd-home.country-lang.x-true.paypal.cmd-login-run.dispatch.5885d80a13c0db1f8e263663d.3faee8d43b1bb6ca6ed6d454adc375ba2d28b99.thebestdir.com/cgi/NaNNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38888:00:00
29456817245836390.00$10,000.00Administrative AssociateCLERICAL ASSOCIATEInternal Audits & DisciplineOverseen by the Office Manager, the Administrative Assistant/Intake Specialist will be responsible for: •\tServing as the frontline receiver of inquiries, communications, and complaints, from the public and Department staff, via telephone, e-mail, and in person; •\tCreating Intake case files, inputting, maintaining, and tracking relevant data; •\tDrafting summaries of complaints, information and reports received via telephone, mail, or email for review by IAD managers; •\tFielding telephone calls and e-mails, while providing prompt and courteous customer service; •\tReferring inquires, information, or complaints to the appropriate IAD staff member, Department unit, or other City agency in a discrete and efficient manner; •\tCreating various reports using various computer applications; •\tProviding administrative support to all employees in the unit, including scheduling, ordering supplies, and assisting with FOIL requests •\tAssisting with office-related issues such as coordinating with Employee Services, Asset Management, and IT for the onboarding of new staff; •\tOverseeing and maintaining the orderly storage of IAD files and archiving case records; •\tMaintaining the unit’s calendars, including scheduling visitors and tracking appointments; •\tSorting, logging and distributing mail to staff accordingly; •\tFaxing, copying and filing documents; •\tPerforming daily clerical functions as needed; •\tUndertaking special projects and tasks as assigned by the Director.Qualification Requirements A four-year high school diploma or its educational equivalent approved by a State's department of education or a recognized accrediting organization and one year of satisfactory clerical experience. Skills Requirement Keyboard familiarity with the ability to type at a minimum of 100 key strokes (20 words) per minute.ERROR: #NAME?ONLY PERMANENT CLERICAL ASSOCIAT WILL BE CONSIDERED This position is open to qualified persons with a disability who are eligible for the 55-a program. Please indicate in your cover letter that you would like to be considered for the position under the 55-a program.For Current City Employees: Visit www.nyc.gov/ess to view and apply for available positions. Click on Recruiting Activities, Careers, and search for the specific Job ID #. No phone calls, faxes or personal inquiries permitted. NOTE: ONLY THOSE CANDIDATES UNDER CONSIDERATION WILL BE CONTACTEDNaNNew York City residency is generally required within 90 days of appointment. However, City Employees in certain titles who have worked for the City for 2 continuous years may also be eligible to reside in Nassau, Suffolk, Putnam, Westchester, Rockland, or Orange County. To determine if the residency requirement applies to you, please discuss with the agency representative at the time of interview.2019-12-16T00:00:00.0002019-12-16T00:00:00.0002019-12-17T00:00:00.000Bachelor�s degree (BA, BS, B.Eng., etc.)Computer science, computer engineering, or software engineering10,000 or more employeesBack-end developer0-2 years0-2 yearsWorking in a different or more specialized technical role than the one I'm in nowI am not interested in new job opportunitiesBetween 2 and 4 years agoA recruiter contacted meConfluence;JiraLess than a monthTaught yourself a new language, framework, or tool without taking a formal courseThe official documentation and/or standards for the technology;Questions & answers on Stack Overflow;Online developer communities other than Stack Overflow (ex. forums, listservs, IRC channels, etc.);The technology�s online help systemNaNNaNAgreeNeither Agree nor DisagreeNeither Agree nor DisagreeGroovy;JavaScript;Python;Bash/ShellGroovy;Java;JavaScript;Python;Bash/ShellNaNAmazon DynamoDB;Amazon RDS/Aurora;ElasticsearchNaNGoogle HomeNode.jsAngular;Node.jsNotepad++;PyCharmWindowsAgile;ScrumGitMultiple times per dayArtificial intelligence surpassing human intelligence ("the singularity")Increasing automation of jobsA governmental or other regulatory bodyI'm worried about the dangers more than I'm excited about the possibilities.25 - 34 years old60 monthsCurrentnhttps://lendingclub.com/browse/loanDetail.action?loan_id=68172458credit_cardCredit card refinancing606xxIL35.90Jul-9819-Feb249.9819-Apr19-Mar3/23/2016 12:07NaNhttps://www.irishtimes.com/life-and-style/food-and-drink/recipes/beetroot-mama-ganoush-1.3999047ppweb.httpxxcwwwhttps.igg.biz/3416785/3416785NaNNaNNaNNaNNaNNaNNaN2017-10-18T16:27:38Z512 Ave U(718) 336-38888:00:00